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"
    }
   },
   "cell_type": "markdown",
   "id": "915fa49f-3d37-4660-9979-a2515f1e4c1d",
   "metadata": {},
   "source": [
    "![image.png](attachment:41228e4f-3c48-4add-ae35-594c64d19466.png)"
   ]
  },
  {
   "attachments": {
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"
    }
   },
   "cell_type": "markdown",
   "id": "c8236e61-e9fb-49aa-ac16-ea2b1732f9f6",
   "metadata": {},
   "source": [
    "# 任务1.1 \n",
    "![image.png](attachment:5e3c21f4-bba2-4561-8fce-e8127b44e34a.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1a8066e3-e32a-467a-afac-d5c8922b97fd",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "cef1948b-2cfd-467e-b182-3f228ca3cdb9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>age</th>\n",
       "      <th>job</th>\n",
       "      <th>marital</th>\n",
       "      <th>education</th>\n",
       "      <th>default</th>\n",
       "      <th>housing</th>\n",
       "      <th>loan</th>\n",
       "      <th>contact</th>\n",
       "      <th>month</th>\n",
       "      <th>day_of_week</th>\n",
       "      <th>duration</th>\n",
       "      <th>poutcome</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BA2200001</td>\n",
       "      <td>56</td>\n",
       "      <td>housemaid</td>\n",
       "      <td>married</td>\n",
       "      <td>postgraduate</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>261</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BA2200002</td>\n",
       "      <td>57</td>\n",
       "      <td>services</td>\n",
       "      <td>married</td>\n",
       "      <td>high school</td>\n",
       "      <td>NaN</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>149</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BA2200077</td>\n",
       "      <td>37</td>\n",
       "      <td>services</td>\n",
       "      <td>married</td>\n",
       "      <td>high school</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>226</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BA2200004</td>\n",
       "      <td>40</td>\n",
       "      <td>admin.</td>\n",
       "      <td>married</td>\n",
       "      <td>postgraduate</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>151</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>BA2200005</td>\n",
       "      <td>56</td>\n",
       "      <td>services</td>\n",
       "      <td>married</td>\n",
       "      <td>high school</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>307</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41171</th>\n",
       "      <td>BA2241172</td>\n",
       "      <td>73</td>\n",
       "      <td>retired</td>\n",
       "      <td>married</td>\n",
       "      <td>junior college</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>nov</td>\n",
       "      <td>fri</td>\n",
       "      <td>334</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41172</th>\n",
       "      <td>BA2241173</td>\n",
       "      <td>46</td>\n",
       "      <td>blue-collar</td>\n",
       "      <td>married</td>\n",
       "      <td>junior college</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>nov</td>\n",
       "      <td>fri</td>\n",
       "      <td>383</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41173</th>\n",
       "      <td>BA2241174</td>\n",
       "      <td>56</td>\n",
       "      <td>retired</td>\n",
       "      <td>married</td>\n",
       "      <td>undergraduate</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>nov</td>\n",
       "      <td>fri</td>\n",
       "      <td>189</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41174</th>\n",
       "      <td>BA2241175</td>\n",
       "      <td>44</td>\n",
       "      <td>technician</td>\n",
       "      <td>married</td>\n",
       "      <td>junior college</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>nov</td>\n",
       "      <td>fri</td>\n",
       "      <td>442</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41175</th>\n",
       "      <td>BA2241176</td>\n",
       "      <td>74</td>\n",
       "      <td>retired</td>\n",
       "      <td>married</td>\n",
       "      <td>junior college</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>nov</td>\n",
       "      <td>fri</td>\n",
       "      <td>239</td>\n",
       "      <td>failure</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>41176 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         user_id  age          job  marital       education default housing  \\\n",
       "0      BA2200001   56    housemaid  married    postgraduate      no      no   \n",
       "1      BA2200002   57     services  married     high school     NaN      no   \n",
       "2      BA2200077   37     services  married     high school      no     yes   \n",
       "3      BA2200004   40       admin.  married    postgraduate      no      no   \n",
       "4      BA2200005   56     services  married     high school      no      no   \n",
       "...          ...  ...          ...      ...             ...     ...     ...   \n",
       "41171  BA2241172   73      retired  married  junior college      no     yes   \n",
       "41172  BA2241173   46  blue-collar  married  junior college      no      no   \n",
       "41173  BA2241174   56      retired  married   undergraduate      no     yes   \n",
       "41174  BA2241175   44   technician  married  junior college      no      no   \n",
       "41175  BA2241176   74      retired  married  junior college      no     yes   \n",
       "\n",
       "      loan    contact month day_of_week  duration     poutcome    y  \n",
       "0       no  telephone   may         mon       261  nonexistent   no  \n",
       "1       no  telephone   may         mon       149  nonexistent   no  \n",
       "2       no  telephone   may         mon       226  nonexistent   no  \n",
       "3       no  telephone   may         mon       151  nonexistent   no  \n",
       "4      yes  telephone   may         mon       307  nonexistent   no  \n",
       "...    ...        ...   ...         ...       ...          ...  ...  \n",
       "41171   no   cellular   nov         fri       334  nonexistent  yes  \n",
       "41172   no   cellular   nov         fri       383  nonexistent   no  \n",
       "41173   no   cellular   nov         fri       189  nonexistent   no  \n",
       "41174   no   cellular   nov         fri       442  nonexistent  yes  \n",
       "41175   no   cellular   nov         fri       239      failure   no  \n",
       "\n",
       "[41176 rows x 14 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sDf=pd.read_csv('B题：银行客户忠诚度分析赛题数据/short-customer-data.csv')\n",
    "sDf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "429da45d-169e-48fa-bfbd-6f3c9f8b4113",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "user_id           0\n",
       "age               0\n",
       "job             330\n",
       "marital          80\n",
       "education      1730\n",
       "default        8596\n",
       "housing         990\n",
       "loan            990\n",
       "contact           0\n",
       "month             0\n",
       "day_of_week       0\n",
       "duration          0\n",
       "poutcome          0\n",
       "y                 0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sDf.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e1be298b-e612-4380-87bf-8c3a5cdbd181",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "69"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sDf[\"user_id\"].duplicated(keep=False).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "ef6b6da2-97c5-41dc-b4c4-b753ef914407",
   "metadata": {},
   "outputs": [],
   "source": [
    "sDf.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "135e138b-ef1d-47c6-af90-253dd2a2e30d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
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       "      <th>user_id</th>\n",
       "      <th>age</th>\n",
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       "      <th>default</th>\n",
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       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BA2200001</td>\n",
       "      <td>56</td>\n",
       "      <td>housemaid</td>\n",
       "      <td>married</td>\n",
       "      <td>postgraduate</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BA2200077</td>\n",
       "      <td>37</td>\n",
       "      <td>services</td>\n",
       "      <td>married</td>\n",
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       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BA2200004</td>\n",
       "      <td>40</td>\n",
       "      <td>admin.</td>\n",
       "      <td>married</td>\n",
       "      <td>postgraduate</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>151</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>BA2200005</td>\n",
       "      <td>56</td>\n",
       "      <td>services</td>\n",
       "      <td>married</td>\n",
       "      <td>high school</td>\n",
       "      <td>no</td>\n",
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       "      <td>yes</td>\n",
       "      <td>telephone</td>\n",
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       "      <td>mon</td>\n",
       "      <td>307</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>BA2200007</td>\n",
       "      <td>59</td>\n",
       "      <td>admin.</td>\n",
       "      <td>married</td>\n",
       "      <td>junior college</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>139</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41171</th>\n",
       "      <td>BA2241172</td>\n",
       "      <td>73</td>\n",
       "      <td>retired</td>\n",
       "      <td>married</td>\n",
       "      <td>junior college</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>nov</td>\n",
       "      <td>fri</td>\n",
       "      <td>334</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41172</th>\n",
       "      <td>BA2241173</td>\n",
       "      <td>46</td>\n",
       "      <td>blue-collar</td>\n",
       "      <td>married</td>\n",
       "      <td>junior college</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>nov</td>\n",
       "      <td>fri</td>\n",
       "      <td>383</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41173</th>\n",
       "      <td>BA2241174</td>\n",
       "      <td>56</td>\n",
       "      <td>retired</td>\n",
       "      <td>married</td>\n",
       "      <td>undergraduate</td>\n",
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       "      <td>yes</td>\n",
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       "      <td>cellular</td>\n",
       "      <td>nov</td>\n",
       "      <td>fri</td>\n",
       "      <td>189</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41174</th>\n",
       "      <td>BA2241175</td>\n",
       "      <td>44</td>\n",
       "      <td>technician</td>\n",
       "      <td>married</td>\n",
       "      <td>junior college</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>nov</td>\n",
       "      <td>fri</td>\n",
       "      <td>442</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41175</th>\n",
       "      <td>BA2241176</td>\n",
       "      <td>74</td>\n",
       "      <td>retired</td>\n",
       "      <td>married</td>\n",
       "      <td>junior college</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>nov</td>\n",
       "      <td>fri</td>\n",
       "      <td>239</td>\n",
       "      <td>failure</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>30478 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         user_id  age          job  marital       education default housing  \\\n",
       "0      BA2200001   56    housemaid  married    postgraduate      no      no   \n",
       "2      BA2200077   37     services  married     high school      no     yes   \n",
       "3      BA2200004   40       admin.  married    postgraduate      no      no   \n",
       "4      BA2200005   56     services  married     high school      no      no   \n",
       "6      BA2200007   59       admin.  married  junior college      no      no   \n",
       "...          ...  ...          ...      ...             ...     ...     ...   \n",
       "41171  BA2241172   73      retired  married  junior college      no     yes   \n",
       "41172  BA2241173   46  blue-collar  married  junior college      no      no   \n",
       "41173  BA2241174   56      retired  married   undergraduate      no     yes   \n",
       "41174  BA2241175   44   technician  married  junior college      no      no   \n",
       "41175  BA2241176   74      retired  married  junior college      no     yes   \n",
       "\n",
       "      loan    contact month day_of_week  duration     poutcome    y  \n",
       "0       no  telephone   may         mon       261  nonexistent   no  \n",
       "2       no  telephone   may         mon       226  nonexistent   no  \n",
       "3       no  telephone   may         mon       151  nonexistent   no  \n",
       "4      yes  telephone   may         mon       307  nonexistent   no  \n",
       "6       no  telephone   may         mon       139  nonexistent   no  \n",
       "...    ...        ...   ...         ...       ...          ...  ...  \n",
       "41171   no   cellular   nov         fri       334  nonexistent  yes  \n",
       "41172   no   cellular   nov         fri       383  nonexistent   no  \n",
       "41173   no   cellular   nov         fri       189  nonexistent   no  \n",
       "41174   no   cellular   nov         fri       442  nonexistent  yes  \n",
       "41175   no   cellular   nov         fri       239      failure   no  \n",
       "\n",
       "[30478 rows x 14 columns]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sDf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "efd5a694-227a-4933-a1d0-7384790e3c1a",
   "metadata": {},
   "outputs": [],
   "source": [
    "sDf.drop_duplicates(subset='user_id',keep=False,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "07118be4-6972-4875-a7d8-6e1cf2fb3ae9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>age</th>\n",
       "      <th>job</th>\n",
       "      <th>marital</th>\n",
       "      <th>education</th>\n",
       "      <th>default</th>\n",
       "      <th>housing</th>\n",
       "      <th>loan</th>\n",
       "      <th>contact</th>\n",
       "      <th>month</th>\n",
       "      <th>day_of_week</th>\n",
       "      <th>duration</th>\n",
       "      <th>poutcome</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BA2200004</td>\n",
       "      <td>40</td>\n",
       "      <td>admin.</td>\n",
       "      <td>married</td>\n",
       "      <td>postgraduate</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>151</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>BA2200005</td>\n",
       "      <td>56</td>\n",
       "      <td>services</td>\n",
       "      <td>married</td>\n",
       "      <td>high school</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>307</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>BA2200007</td>\n",
       "      <td>59</td>\n",
       "      <td>admin.</td>\n",
       "      <td>married</td>\n",
       "      <td>junior college</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>139</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>BA2200009</td>\n",
       "      <td>24</td>\n",
       "      <td>technician</td>\n",
       "      <td>single</td>\n",
       "      <td>junior college</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>380</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>BA2200010</td>\n",
       "      <td>25</td>\n",
       "      <td>services</td>\n",
       "      <td>single</td>\n",
       "      <td>high school</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>50</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41170</th>\n",
       "      <td>BA2241171</td>\n",
       "      <td>29</td>\n",
       "      <td>unemployed</td>\n",
       "      <td>single</td>\n",
       "      <td>postgraduate</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>nov</td>\n",
       "      <td>fri</td>\n",
       "      <td>112</td>\n",
       "      <td>success</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41172</th>\n",
       "      <td>BA2241173</td>\n",
       "      <td>46</td>\n",
       "      <td>blue-collar</td>\n",
       "      <td>married</td>\n",
       "      <td>junior college</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>nov</td>\n",
       "      <td>fri</td>\n",
       "      <td>383</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41173</th>\n",
       "      <td>BA2241174</td>\n",
       "      <td>56</td>\n",
       "      <td>retired</td>\n",
       "      <td>married</td>\n",
       "      <td>undergraduate</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>nov</td>\n",
       "      <td>fri</td>\n",
       "      <td>189</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41174</th>\n",
       "      <td>BA2241175</td>\n",
       "      <td>44</td>\n",
       "      <td>technician</td>\n",
       "      <td>married</td>\n",
       "      <td>junior college</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>nov</td>\n",
       "      <td>fri</td>\n",
       "      <td>442</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41175</th>\n",
       "      <td>BA2241176</td>\n",
       "      <td>74</td>\n",
       "      <td>retired</td>\n",
       "      <td>married</td>\n",
       "      <td>junior college</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>nov</td>\n",
       "      <td>fri</td>\n",
       "      <td>239</td>\n",
       "      <td>failure</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>30436 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         user_id  age          job  marital       education default housing  \\\n",
       "3      BA2200004   40       admin.  married    postgraduate      no      no   \n",
       "4      BA2200005   56     services  married     high school      no      no   \n",
       "6      BA2200007   59       admin.  married  junior college      no      no   \n",
       "8      BA2200009   24   technician   single  junior college      no     yes   \n",
       "9      BA2200010   25     services   single     high school      no     yes   \n",
       "...          ...  ...          ...      ...             ...     ...     ...   \n",
       "41170  BA2241171   29   unemployed   single    postgraduate      no     yes   \n",
       "41172  BA2241173   46  blue-collar  married  junior college      no      no   \n",
       "41173  BA2241174   56      retired  married   undergraduate      no     yes   \n",
       "41174  BA2241175   44   technician  married  junior college      no      no   \n",
       "41175  BA2241176   74      retired  married  junior college      no     yes   \n",
       "\n",
       "      loan    contact month day_of_week  duration     poutcome    y  \n",
       "3       no  telephone   may         mon       151  nonexistent   no  \n",
       "4      yes  telephone   may         mon       307  nonexistent   no  \n",
       "6       no  telephone   may         mon       139  nonexistent   no  \n",
       "8       no  telephone   may         mon       380  nonexistent   no  \n",
       "9       no  telephone   may         mon        50  nonexistent   no  \n",
       "...    ...        ...   ...         ...       ...          ...  ...  \n",
       "41170   no   cellular   nov         fri       112      success   no  \n",
       "41172   no   cellular   nov         fri       383  nonexistent   no  \n",
       "41173   no   cellular   nov         fri       189  nonexistent   no  \n",
       "41174   no   cellular   nov         fri       442  nonexistent  yes  \n",
       "41175   no   cellular   nov         fri       239      failure   no  \n",
       "\n",
       "[30436 rows x 14 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sDf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "baa8d850-fbdb-4748-8faf-da9698d05f9c",
   "metadata": {},
   "outputs": [],
   "source": [
    "sDf.to_excel('result1_1.xlsx',index=False)"
   ]
  },
  {
   "attachments": {
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     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "eff357db-d345-46c7-9ca1-34813b8ef86a",
   "metadata": {},
   "source": [
    "![image.png](attachment:aa7b56cd-4efa-4990-9eef-4a30ef4017c2.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "d8ae6ea6-8daa-443f-a23e-50b78565a1b6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CustomerId</th>\n",
       "      <th>CreditScore</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Tenure</th>\n",
       "      <th>Balance</th>\n",
       "      <th>NumOfProducts</th>\n",
       "      <th>HasCrCard</th>\n",
       "      <th>IsActiveMember</th>\n",
       "      <th>EstimatedSalary</th>\n",
       "      <th>Exited</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
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       "      <td>79866.73</td>\n",
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       "      <td>15553283</td>\n",
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       "      <td>91611.12</td>\n",
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       "      <td>188150.60</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>9295</th>\n",
       "      <td>15815628</td>\n",
       "      <td>711</td>\n",
       "      <td>1</td>\n",
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       "      <td>8</td>\n",
       "      <td>113899.92</td>\n",
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       "      <td>0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>9296</th>\n",
       "      <td>15815645</td>\n",
       "      <td>481</td>\n",
       "      <td>0</td>\n",
       "      <td>37</td>\n",
       "      <td>8</td>\n",
       "      <td>152303.66</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>175082.20</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9297</th>\n",
       "      <td>15815656</td>\n",
       "      <td>541</td>\n",
       "      <td>1</td>\n",
       "      <td>39</td>\n",
       "      <td>9</td>\n",
       "      <td>100116.67</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>199808.10</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9298</th>\n",
       "      <td>15815660</td>\n",
       "      <td>758</td>\n",
       "      <td>1</td>\n",
       "      <td>34</td>\n",
       "      <td>1</td>\n",
       "      <td>154139.45</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>60728.89</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9299</th>\n",
       "      <td>15815690</td>\n",
       "      <td>614</td>\n",
       "      <td>1</td>\n",
       "      <td>40</td>\n",
       "      <td>3</td>\n",
       "      <td>113348.50</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>77789.01</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9300 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      CustomerId  CreditScore  Gender Age  Tenure    Balance  NumOfProducts  \\\n",
       "0       15553251          713       1  52       0  185891.54              1   \n",
       "1       15553256          619       1  41       8       0.00              3   \n",
       "2       15553283          603       1  42       8   91611.12              1   \n",
       "3       15553308          589       1  61       1       0.00              1   \n",
       "4       15553387          687       1  39       2       0.00              3   \n",
       "...          ...          ...     ...  ..     ...        ...            ...   \n",
       "9295    15815628          711       1  37       8  113899.92              1   \n",
       "9296    15815645          481       0  37       8  152303.66              2   \n",
       "9297    15815656          541       1  39       9  100116.67              1   \n",
       "9298    15815660          758       1  34       1  154139.45              1   \n",
       "9299    15815690          614       1  40       3  113348.50              1   \n",
       "\n",
       "      HasCrCard  IsActiveMember  EstimatedSalary  Exited  \n",
       "0             1               1         46369.57       1  \n",
       "1             1               1         79866.73       1  \n",
       "2             0               0        144675.30       1  \n",
       "3             1               0         61108.56       1  \n",
       "4             0               0        188150.60       1  \n",
       "...         ...             ...              ...     ...  \n",
       "9295          0               0         80215.20       0  \n",
       "9296          1               1        175082.20       0  \n",
       "9297          1               1        199808.10       1  \n",
       "9298          1               1         60728.89       0  \n",
       "9299          1               1         77789.01       0  \n",
       "\n",
       "[9300 rows x 11 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lDf=pd.read_csv('B题：银行客户忠诚度分析赛题数据/long-customer-train.csv')\n",
    "lDf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "dc175bf1-94c2-4f89-9862-835c6baacdbd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['-',\n",
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       " '21 岁',\n",
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       " '23岁 ',\n",
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       " '27',\n",
       " '27岁',\n",
       " '27岁 ',\n",
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       " '33岁 ',\n",
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       " '34 岁',\n",
       " '34岁',\n",
       " '34岁 ',\n",
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       " '37',\n",
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       " '39',\n",
       " '40',\n",
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       " '42',\n",
       " '43',\n",
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       " '45',\n",
       " '45 岁',\n",
       " '45岁',\n",
       " '45岁 ',\n",
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       " '46 岁',\n",
       " '47',\n",
       " '47 岁',\n",
       " '47岁 ',\n",
       " '48',\n",
       " '49',\n",
       " '49 岁',\n",
       " '49岁',\n",
       " '50',\n",
       " '50 岁',\n",
       " '51',\n",
       " '52',\n",
       " '53',\n",
       " '54',\n",
       " '55',\n",
       " '56',\n",
       " '57',\n",
       " '57岁 ',\n",
       " '58',\n",
       " '59',\n",
       " '60',\n",
       " '61',\n",
       " '62',\n",
       " '62 岁',\n",
       " '62岁 ',\n",
       " '63',\n",
       " '63 岁',\n",
       " '63岁',\n",
       " '64',\n",
       " '64岁 ',\n",
       " '65',\n",
       " '66',\n",
       " '66岁 ',\n",
       " '67',\n",
       " '68',\n",
       " '69',\n",
       " '70',\n",
       " '71',\n",
       " '72',\n",
       " '73',\n",
       " '73岁 ',\n",
       " '74',\n",
       " '75',\n",
       " '76',\n",
       " '77',\n",
       " '77岁 ',\n",
       " '78',\n",
       " '79',\n",
       " '80',\n",
       " '81',\n",
       " '82',\n",
       " '83',\n",
       " '84',\n",
       " '88',\n",
       " '92']"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 获取并显示Age有多少种不同取值\n",
    "lDf.groupby('Age').count().index.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "4748223a-4b90-43a8-b46d-155808b59554",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index([ 464,  566,  651,  696,  796,  914, 1064, 1066, 1112, 1211,\n",
       "       ...\n",
       "       8077, 8176, 8270, 8442, 8591, 8723, 8776, 8794, 8836, 9238],\n",
       "      dtype='int64', length=102)"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 获取所有Age中存在['-1','0','-']的行索引名\n",
    "delILi=lDf[lDf['Age'].isin(['-1','0','-'])].index\n",
    "delILi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "20b2f65d-6317-486e-af35-1af70d74f969",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CustomerId</th>\n",
       "      <th>CreditScore</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Tenure</th>\n",
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       "      <td>79866.73</td>\n",
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       "      <td>15553308</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>9295</th>\n",
       "      <td>15815628</td>\n",
       "      <td>711</td>\n",
       "      <td>1</td>\n",
       "      <td>37</td>\n",
       "      <td>8</td>\n",
       "      <td>113899.92</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "      <td>80215.20</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>9296</th>\n",
       "      <td>15815645</td>\n",
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       "      <td>8</td>\n",
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       "    <tr>\n",
       "      <th>9297</th>\n",
       "      <td>15815656</td>\n",
       "      <td>541</td>\n",
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       "      <td>9</td>\n",
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       "      <td>1</td>\n",
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       "      <td>34</td>\n",
       "      <td>1</td>\n",
       "      <td>154139.45</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>9198 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      CustomerId  CreditScore  Gender Age  Tenure    Balance  NumOfProducts  \\\n",
       "0       15553251          713       1  52       0  185891.54              1   \n",
       "1       15553256          619       1  41       8       0.00              3   \n",
       "2       15553283          603       1  42       8   91611.12              1   \n",
       "3       15553308          589       1  61       1       0.00              1   \n",
       "4       15553387          687       1  39       2       0.00              3   \n",
       "...          ...          ...     ...  ..     ...        ...            ...   \n",
       "9295    15815628          711       1  37       8  113899.92              1   \n",
       "9296    15815645          481       0  37       8  152303.66              2   \n",
       "9297    15815656          541       1  39       9  100116.67              1   \n",
       "9298    15815660          758       1  34       1  154139.45              1   \n",
       "9299    15815690          614       1  40       3  113348.50              1   \n",
       "\n",
       "      HasCrCard  IsActiveMember  EstimatedSalary  Exited  \n",
       "0             1               1         46369.57       1  \n",
       "1             1               1         79866.73       1  \n",
       "2             0               0        144675.30       1  \n",
       "3             1               0         61108.56       1  \n",
       "4             0               0        188150.60       1  \n",
       "...         ...             ...              ...     ...  \n",
       "9295          0               0         80215.20       0  \n",
       "9296          1               1        175082.20       0  \n",
       "9297          1               1        199808.10       1  \n",
       "9298          1               1         60728.89       0  \n",
       "9299          1               1         77789.01       0  \n",
       "\n",
       "[9198 rows x 11 columns]"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lDf.drop(delILi,inplace=True)\n",
    "lDf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "0e9f0f34-3221-4ea1-ac31-eca34365047f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['1',\n",
       " '18',\n",
       " '19',\n",
       " '20',\n",
       " '20岁',\n",
       " '21',\n",
       " '21 岁',\n",
       " '22',\n",
       " '22 岁',\n",
       " '23',\n",
       " '23岁 ',\n",
       " '24',\n",
       " '24岁 ',\n",
       " '25',\n",
       " '25 岁',\n",
       " '25岁 ',\n",
       " '26',\n",
       " '26 岁',\n",
       " '26岁',\n",
       " '26岁 ',\n",
       " '27',\n",
       " '27岁',\n",
       " '27岁 ',\n",
       " '28',\n",
       " '28 岁',\n",
       " '29',\n",
       " '29岁',\n",
       " '29岁 ',\n",
       " '30',\n",
       " '30 岁',\n",
       " '30岁 ',\n",
       " '31',\n",
       " '31 岁',\n",
       " '31岁',\n",
       " '31岁 ',\n",
       " '32',\n",
       " '32 岁',\n",
       " '32岁',\n",
       " '33',\n",
       " '33 岁',\n",
       " '33岁',\n",
       " '33岁 ',\n",
       " '34',\n",
       " '34 岁',\n",
       " '34岁',\n",
       " '34岁 ',\n",
       " '35',\n",
       " '36',\n",
       " '37',\n",
       " '38',\n",
       " '39',\n",
       " '40',\n",
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       " '44',\n",
       " '45',\n",
       " '45 岁',\n",
       " '45岁',\n",
       " '45岁 ',\n",
       " '46',\n",
       " '46 岁',\n",
       " '47',\n",
       " '47 岁',\n",
       " '47岁 ',\n",
       " '48',\n",
       " '49',\n",
       " '49 岁',\n",
       " '49岁',\n",
       " '50',\n",
       " '50 岁',\n",
       " '51',\n",
       " '52',\n",
       " '53',\n",
       " '54',\n",
       " '55',\n",
       " '56',\n",
       " '57',\n",
       " '57岁 ',\n",
       " '58',\n",
       " '59',\n",
       " '60',\n",
       " '61',\n",
       " '62',\n",
       " '62 岁',\n",
       " '62岁 ',\n",
       " '63',\n",
       " '63 岁',\n",
       " '63岁',\n",
       " '64',\n",
       " '64岁 ',\n",
       " '65',\n",
       " '66',\n",
       " '66岁 ',\n",
       " '67',\n",
       " '68',\n",
       " '69',\n",
       " '70',\n",
       " '71',\n",
       " '72',\n",
       " '73',\n",
       " '73岁 ',\n",
       " '74',\n",
       " '75',\n",
       " '76',\n",
       " '77',\n",
       " '77岁 ',\n",
       " '78',\n",
       " '79',\n",
       " '80',\n",
       " '81',\n",
       " '82',\n",
       " '83',\n",
       " '84',\n",
       " '88',\n",
       " '92']"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 再获取并显示Age有多少种不同取值\n",
    "lDf.groupby('Age').count().index.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "e04165e6-1b5b-4a84-b432-790a3c2e025f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       52\n",
       "1       41\n",
       "2       42\n",
       "3       61\n",
       "4       39\n",
       "        ..\n",
       "9295    37\n",
       "9296    37\n",
       "9297    39\n",
       "9298    34\n",
       "9299    40\n",
       "Name: Age, Length: 9198, dtype: object"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "correctAgeSer=lDf['Age'].str.replace('岁','')\n",
    "correctAgeSer=correctAgeSer.str.replace(' ','')\n",
    "correctAgeSer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "ba5a3272-37c4-438b-b96c-ecf927dde3ed",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<p>9198 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      CustomerId  CreditScore  Gender Age  Tenure    Balance  NumOfProducts  \\\n",
       "0       15553251          713       1  52       0  185891.54              1   \n",
       "1       15553256          619       1  41       8       0.00              3   \n",
       "2       15553283          603       1  42       8   91611.12              1   \n",
       "3       15553308          589       1  61       1       0.00              1   \n",
       "4       15553387          687       1  39       2       0.00              3   \n",
       "...          ...          ...     ...  ..     ...        ...            ...   \n",
       "9295    15815628          711       1  37       8  113899.92              1   \n",
       "9296    15815645          481       0  37       8  152303.66              2   \n",
       "9297    15815656          541       1  39       9  100116.67              1   \n",
       "9298    15815660          758       1  34       1  154139.45              1   \n",
       "9299    15815690          614       1  40       3  113348.50              1   \n",
       "\n",
       "      HasCrCard  IsActiveMember  EstimatedSalary  Exited  \n",
       "0             1               1         46369.57       1  \n",
       "1             1               1         79866.73       1  \n",
       "2             0               0        144675.30       1  \n",
       "3             1               0         61108.56       1  \n",
       "4             0               0        188150.60       1  \n",
       "...         ...             ...              ...     ...  \n",
       "9295          0               0         80215.20       0  \n",
       "9296          1               1        175082.20       0  \n",
       "9297          1               1        199808.10       1  \n",
       "9298          1               1         60728.89       0  \n",
       "9299          1               1         77789.01       0  \n",
       "\n",
       "[9198 rows x 11 columns]"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lDf['Age']=correctAgeSer\n",
    "lDf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "8b87e397-4131-4830-a29a-64ff702b6e2f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['1',\n",
       " '18',\n",
       " '19',\n",
       " '20',\n",
       " '21',\n",
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       " '65',\n",
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       " '72',\n",
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       " '74',\n",
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       " '76',\n",
       " '77',\n",
       " '78',\n",
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       " '80',\n",
       " '81',\n",
       " '82',\n",
       " '83',\n",
       " '84',\n",
       " '88',\n",
       " '92']"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lDf.groupby('Age').count().index.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "0b01645b-7fa5-4c78-8a1a-db6ed301a904",
   "metadata": {},
   "outputs": [],
   "source": [
    "lDf.to_excel('result1_2.xlsx',index=False)"
   ]
  },
  {
   "attachments": {
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"
    }
   },
   "cell_type": "markdown",
   "id": "f39ab982-68f5-401a-967e-4cee76d1a788",
   "metadata": {},
   "source": [
    "![image.png](attachment:97f2b45a-af03-4ed5-9439-5c7ffddca581.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "id": "4004783d-222b-490f-8a40-7fff3b55ef6f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>age</th>\n",
       "      <th>job</th>\n",
       "      <th>marital</th>\n",
       "      <th>education</th>\n",
       "      <th>default</th>\n",
       "      <th>housing</th>\n",
       "      <th>loan</th>\n",
       "      <th>contact</th>\n",
       "      <th>month</th>\n",
       "      <th>day_of_week</th>\n",
       "      <th>duration</th>\n",
       "      <th>poutcome</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BA2200004</td>\n",
       "      <td>40</td>\n",
       "      <td>admin.</td>\n",
       "      <td>married</td>\n",
       "      <td>postgraduate</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>151</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BA2200005</td>\n",
       "      <td>56</td>\n",
       "      <td>services</td>\n",
       "      <td>married</td>\n",
       "      <td>high school</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>307</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BA2200007</td>\n",
       "      <td>59</td>\n",
       "      <td>admin.</td>\n",
       "      <td>married</td>\n",
       "      <td>junior college</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>139</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BA2200009</td>\n",
       "      <td>24</td>\n",
       "      <td>technician</td>\n",
       "      <td>single</td>\n",
       "      <td>junior college</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>380</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>BA2200010</td>\n",
       "      <td>25</td>\n",
       "      <td>services</td>\n",
       "      <td>single</td>\n",
       "      <td>high school</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>telephone</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>50</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30431</th>\n",
       "      <td>BA2241171</td>\n",
       "      <td>29</td>\n",
       "      <td>unemployed</td>\n",
       "      <td>single</td>\n",
       "      <td>postgraduate</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>nov</td>\n",
       "      <td>fri</td>\n",
       "      <td>112</td>\n",
       "      <td>success</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30432</th>\n",
       "      <td>BA2241173</td>\n",
       "      <td>46</td>\n",
       "      <td>blue-collar</td>\n",
       "      <td>married</td>\n",
       "      <td>junior college</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>nov</td>\n",
       "      <td>fri</td>\n",
       "      <td>383</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30433</th>\n",
       "      <td>BA2241174</td>\n",
       "      <td>56</td>\n",
       "      <td>retired</td>\n",
       "      <td>married</td>\n",
       "      <td>undergraduate</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>nov</td>\n",
       "      <td>fri</td>\n",
       "      <td>189</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30434</th>\n",
       "      <td>BA2241175</td>\n",
       "      <td>44</td>\n",
       "      <td>technician</td>\n",
       "      <td>married</td>\n",
       "      <td>junior college</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>nov</td>\n",
       "      <td>fri</td>\n",
       "      <td>442</td>\n",
       "      <td>nonexistent</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30435</th>\n",
       "      <td>BA2241176</td>\n",
       "      <td>74</td>\n",
       "      <td>retired</td>\n",
       "      <td>married</td>\n",
       "      <td>junior college</td>\n",
       "      <td>no</td>\n",
       "      <td>yes</td>\n",
       "      <td>no</td>\n",
       "      <td>cellular</td>\n",
       "      <td>nov</td>\n",
       "      <td>fri</td>\n",
       "      <td>239</td>\n",
       "      <td>failure</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>30436 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         user_id  age          job  marital       education default housing  \\\n",
       "0      BA2200004   40       admin.  married    postgraduate      no      no   \n",
       "1      BA2200005   56     services  married     high school      no      no   \n",
       "2      BA2200007   59       admin.  married  junior college      no      no   \n",
       "3      BA2200009   24   technician   single  junior college      no     yes   \n",
       "4      BA2200010   25     services   single     high school      no     yes   \n",
       "...          ...  ...          ...      ...             ...     ...     ...   \n",
       "30431  BA2241171   29   unemployed   single    postgraduate      no     yes   \n",
       "30432  BA2241173   46  blue-collar  married  junior college      no      no   \n",
       "30433  BA2241174   56      retired  married   undergraduate      no     yes   \n",
       "30434  BA2241175   44   technician  married  junior college      no      no   \n",
       "30435  BA2241176   74      retired  married  junior college      no     yes   \n",
       "\n",
       "      loan    contact month day_of_week  duration     poutcome    y  \n",
       "0       no  telephone   may         mon       151  nonexistent   no  \n",
       "1      yes  telephone   may         mon       307  nonexistent   no  \n",
       "2       no  telephone   may         mon       139  nonexistent   no  \n",
       "3       no  telephone   may         mon       380  nonexistent   no  \n",
       "4       no  telephone   may         mon        50  nonexistent   no  \n",
       "...    ...        ...   ...         ...       ...          ...  ...  \n",
       "30431   no   cellular   nov         fri       112      success   no  \n",
       "30432   no   cellular   nov         fri       383  nonexistent   no  \n",
       "30433   no   cellular   nov         fri       189  nonexistent   no  \n",
       "30434   no   cellular   nov         fri       442  nonexistent  yes  \n",
       "30435   no   cellular   nov         fri       239      failure   no  \n",
       "\n",
       "[30436 rows x 14 columns]"
      ]
     },
     "execution_count": 180,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sDf=pd.read_excel('result1_1.xlsx')\n",
    "sDf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "id": "d6e53801-6b9d-435d-8446-57d21e959a34",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "def changeFeatureCoding(ser):\n",
    "    \n",
    "    uqSer=ser.unique()\n",
    "    newLi=range(uqSer.shape[0])\n",
    "    for i in range(len(newLi)):\n",
    "        print(f'{uqSer[i]:15s}={newLi[i]}')\n",
    "    \n",
    "    return ser.replace(uqSer,newLi)\n",
    "\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "id": "654e8a2d-3e5f-4478-a18f-eb4b3c8978dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['admin.', 'services', 'technician', 'blue-collar', 'housemaid',\n",
       "       'unemployed', 'retired', 'entrepreneur', 'management', 'student',\n",
       "       'self-employed'], dtype=object)"
      ]
     },
     "execution_count": 182,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sDf['job'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "id": "de7a1943-c951-46fa-84b7-f1f114a900c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['married', 'single', 'divorced'], dtype=object)"
      ]
     },
     "execution_count": 183,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sDf['marital'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "id": "b3fbb48d-1120-438f-b75f-d768d0b9c79b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['postgraduate', 'high school', 'junior college', 'undergraduate',\n",
       "       'illiterate'], dtype=object)"
      ]
     },
     "execution_count": 184,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sDf['education'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "id": "d3141432-4864-4b77-8df6-8932056848e6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['no', 'yes'], dtype=object)"
      ]
     },
     "execution_count": 185,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sDf['default'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "id": "e5e13dac-cdfc-42aa-b11f-644676db820f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['no', 'yes'], dtype=object)"
      ]
     },
     "execution_count": 186,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sDf['housing'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "id": "b71e687c-05db-42bd-9af6-309dc5725983",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['no', 'yes'], dtype=object)"
      ]
     },
     "execution_count": 187,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sDf['loan'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "id": "f14e1154-fabc-4c5c-af2c-ce2be32d8d8c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['telephone', 'cellular'], dtype=object)"
      ]
     },
     "execution_count": 188,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sDf['contact'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "id": "9dea3127-1f33-4ba8-bb07-0ee7e35e78e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['nonexistent', 'failure', 'success'], dtype=object)"
      ]
     },
     "execution_count": 189,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sDf['poutcome'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "id": "9603581b-fd94-4eb1-88a8-a5ec180888f3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['no', 'yes'], dtype=object)"
      ]
     },
     "execution_count": 190,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sDf['y'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "id": "7593a137-745e-4df7-9d05-2d7d694bf026",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "索引列名：job\n",
      "admin.         =0\n",
      "services       =1\n",
      "technician     =2\n",
      "blue-collar    =3\n",
      "housemaid      =4\n",
      "unemployed     =5\n",
      "retired        =6\n",
      "entrepreneur   =7\n",
      "management     =8\n",
      "student        =9\n",
      "self-employed  =10\n",
      "\n",
      "\n",
      "索引列名：marital\n",
      "married        =0\n",
      "single         =1\n",
      "divorced       =2\n",
      "\n",
      "\n",
      "索引列名：education\n",
      "postgraduate   =0\n",
      "high school    =1\n",
      "junior college =2\n",
      "undergraduate  =3\n",
      "illiterate     =4\n",
      "\n",
      "\n",
      "索引列名：default\n",
      "no             =0\n",
      "yes            =1\n",
      "\n",
      "\n",
      "索引列名：housing\n",
      "no             =0\n",
      "yes            =1\n",
      "\n",
      "\n",
      "索引列名：loan\n",
      "no             =0\n",
      "yes            =1\n",
      "\n",
      "\n",
      "索引列名：contact\n",
      "telephone      =0\n",
      "cellular       =1\n",
      "\n",
      "\n",
      "索引列名：poutcome\n",
      "nonexistent    =0\n",
      "failure        =1\n",
      "success        =2\n",
      "\n",
      "\n",
      "索引列名：y\n",
      "no             =0\n",
      "yes            =1\n"
     ]
    }
   ],
   "source": [
    "print('索引列名：job')\n",
    "sDf['job']=changeFeatureCoding(sDf['job'])\n",
    "print(\"\\n\\n索引列名：marital\")\n",
    "sDf['marital']=changeFeatureCoding(sDf['marital'])\n",
    "print(\"\\n\\n索引列名：education\")\n",
    "sDf['education']=changeFeatureCoding(sDf['education'])\n",
    "print(\"\\n\\n索引列名：default\")\n",
    "sDf['default']=changeFeatureCoding(sDf['default'])\n",
    "print(\"\\n\\n索引列名：housing\")\n",
    "sDf['housing']=changeFeatureCoding(sDf['housing'])\n",
    "print(\"\\n\\n索引列名：loan\")\n",
    "sDf['loan']=changeFeatureCoding(sDf['loan'])\n",
    "print(\"\\n\\n索引列名：contact\")\n",
    "sDf['contact']=changeFeatureCoding(sDf['contact'])\n",
    "print(\"\\n\\n索引列名：poutcome\")\n",
    "sDf['poutcome']=changeFeatureCoding(sDf['poutcome'])\n",
    "print(\"\\n\\n索引列名：y\")\n",
    "sDf['y']=changeFeatureCoding(sDf['y'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "id": "f59cb28d-0f07-4268-8f77-68bcc5fedcc9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>age</th>\n",
       "      <th>job</th>\n",
       "      <th>marital</th>\n",
       "      <th>education</th>\n",
       "      <th>default</th>\n",
       "      <th>housing</th>\n",
       "      <th>loan</th>\n",
       "      <th>contact</th>\n",
       "      <th>month</th>\n",
       "      <th>day_of_week</th>\n",
       "      <th>duration</th>\n",
       "      <th>poutcome</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BA2200004</td>\n",
       "      <td>40</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>151</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BA2200005</td>\n",
       "      <td>56</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>307</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BA2200007</td>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BA2200009</td>\n",
       "      <td>24</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>380</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>BA2200010</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>may</td>\n",
       "      <td>mon</td>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30431</th>\n",
       "      <td>BA2241171</td>\n",
       "      <td>29</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>nov</td>\n",
       "      <td>fri</td>\n",
       "      <td>112</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30432</th>\n",
       "      <td>BA2241173</td>\n",
       "      <td>46</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>nov</td>\n",
       "      <td>fri</td>\n",
       "      <td>383</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30433</th>\n",
       "      <td>BA2241174</td>\n",
       "      <td>56</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>nov</td>\n",
       "      <td>fri</td>\n",
       "      <td>189</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30434</th>\n",
       "      <td>BA2241175</td>\n",
       "      <td>44</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>nov</td>\n",
       "      <td>fri</td>\n",
       "      <td>442</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30435</th>\n",
       "      <td>BA2241176</td>\n",
       "      <td>74</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>nov</td>\n",
       "      <td>fri</td>\n",
       "      <td>239</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>30436 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         user_id  age  job  marital  education  default  housing  loan  \\\n",
       "0      BA2200004   40    0        0          0        0        0     0   \n",
       "1      BA2200005   56    1        0          1        0        0     1   \n",
       "2      BA2200007   59    0        0          2        0        0     0   \n",
       "3      BA2200009   24    2        1          2        0        1     0   \n",
       "4      BA2200010   25    1        1          1        0        1     0   \n",
       "...          ...  ...  ...      ...        ...      ...      ...   ...   \n",
       "30431  BA2241171   29    5        1          0        0        1     0   \n",
       "30432  BA2241173   46    3        0          2        0        0     0   \n",
       "30433  BA2241174   56    6        0          3        0        1     0   \n",
       "30434  BA2241175   44    2        0          2        0        0     0   \n",
       "30435  BA2241176   74    6        0          2        0        1     0   \n",
       "\n",
       "       contact month day_of_week  duration  poutcome  y  \n",
       "0            0   may         mon       151         0  0  \n",
       "1            0   may         mon       307         0  0  \n",
       "2            0   may         mon       139         0  0  \n",
       "3            0   may         mon       380         0  0  \n",
       "4            0   may         mon        50         0  0  \n",
       "...        ...   ...         ...       ...       ... ..  \n",
       "30431        1   nov         fri       112         2  0  \n",
       "30432        1   nov         fri       383         0  0  \n",
       "30433        1   nov         fri       189         0  0  \n",
       "30434        1   nov         fri       442         0  1  \n",
       "30435        1   nov         fri       239         1  0  \n",
       "\n",
       "[30436 rows x 14 columns]"
      ]
     },
     "execution_count": 192,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sDf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "id": "acbf5141-d918-473d-b5ac-af8c579845ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['may', 'jun', 'jul', 'aug', 'oct', 'nov', 'dec', 'mar', 'apr',\n",
       "       'sep'], dtype=object)"
      ]
     },
     "execution_count": 193,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sDf['month'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "id": "dd104935-ccbf-472f-a215-ad4688f887ed",
   "metadata": {},
   "outputs": [],
   "source": [
    "monli=[5,6,7,8,10,11,12,3,4,9]\n",
    "sDf['month']=sDf['month'].replace(sDf['month'].unique(),monli)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "id": "d4e7b12b-2f72-455c-b5cb-f54960292198",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['mon', 'tue', 'wed', 'thu', 'fri'], dtype=object)"
      ]
     },
     "execution_count": 196,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sDf['day_of_week'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "id": "eb4373d9-ea5f-43cf-aa70-50a71d664180",
   "metadata": {},
   "outputs": [],
   "source": [
    "dorwli=[1,2,3,4,5]\n",
    "sDf['day_of_week']=sDf['day_of_week'].replace(sDf['day_of_week'].unique(),dorwli)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "id": "38d390e1-c03d-4377-b180-eca976d1a35d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>age</th>\n",
       "      <th>job</th>\n",
       "      <th>marital</th>\n",
       "      <th>education</th>\n",
       "      <th>default</th>\n",
       "      <th>housing</th>\n",
       "      <th>loan</th>\n",
       "      <th>contact</th>\n",
       "      <th>month</th>\n",
       "      <th>day_of_week</th>\n",
       "      <th>duration</th>\n",
       "      <th>poutcome</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>BA2200004</td>\n",
       "      <td>40</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>151</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>BA2200005</td>\n",
       "      <td>56</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>307</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BA2200007</td>\n",
       "      <td>59</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>139</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>BA2200009</td>\n",
       "      <td>24</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>380</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>BA2200010</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30431</th>\n",
       "      <td>BA2241171</td>\n",
       "      <td>29</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>5</td>\n",
       "      <td>112</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30432</th>\n",
       "      <td>BA2241173</td>\n",
       "      <td>46</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>5</td>\n",
       "      <td>383</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30433</th>\n",
       "      <td>BA2241174</td>\n",
       "      <td>56</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>5</td>\n",
       "      <td>189</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30434</th>\n",
       "      <td>BA2241175</td>\n",
       "      <td>44</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>5</td>\n",
       "      <td>442</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30435</th>\n",
       "      <td>BA2241176</td>\n",
       "      <td>74</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>11</td>\n",
       "      <td>5</td>\n",
       "      <td>239</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>30436 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         user_id  age  job  marital  education  default  housing  loan  \\\n",
       "0      BA2200004   40    0        0          0        0        0     0   \n",
       "1      BA2200005   56    1        0          1        0        0     1   \n",
       "2      BA2200007   59    0        0          2        0        0     0   \n",
       "3      BA2200009   24    2        1          2        0        1     0   \n",
       "4      BA2200010   25    1        1          1        0        1     0   \n",
       "...          ...  ...  ...      ...        ...      ...      ...   ...   \n",
       "30431  BA2241171   29    5        1          0        0        1     0   \n",
       "30432  BA2241173   46    3        0          2        0        0     0   \n",
       "30433  BA2241174   56    6        0          3        0        1     0   \n",
       "30434  BA2241175   44    2        0          2        0        0     0   \n",
       "30435  BA2241176   74    6        0          2        0        1     0   \n",
       "\n",
       "       contact  month  day_of_week  duration  poutcome  y  \n",
       "0            0      5            1       151         0  0  \n",
       "1            0      5            1       307         0  0  \n",
       "2            0      5            1       139         0  0  \n",
       "3            0      5            1       380         0  0  \n",
       "4            0      5            1        50         0  0  \n",
       "...        ...    ...          ...       ...       ... ..  \n",
       "30431        1     11            5       112         2  0  \n",
       "30432        1     11            5       383         0  0  \n",
       "30433        1     11            5       189         0  0  \n",
       "30434        1     11            5       442         0  1  \n",
       "30435        1     11            5       239         1  0  \n",
       "\n",
       "[30436 rows x 14 columns]"
      ]
     },
     "execution_count": 199,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sDf"
   ]
  },
  {
   "attachments": {
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pGtDB53Bb4Q68mra6H9Qyq11M/xbj+pu3RqN3vV+zzOR5dCf9d2H10PuU2C8tfdtftW9PHLjxEN/KA5tfEK7Z/zeEHY35b/zmHOO/ehjdbtircx3Ymz67cRr4IAmQQB0JVE9kHuYQlXJyj0Fpxgj33+dtDL4UeWeJN931q9elEfAiCZAACZDAOgLVE5l1FvE+CZAACZDA3hCgyOxNVjAhJEACJFA/AhSZ+uUpLSIBEiCBvSFAkdmbrGBCSIAESKB+BCgy9ctTWkQCJEACe0OAIrM3WcGEkAAJkED9CFBk6pentIgESIAE9oYARWZvsoIJIQESIIH6EaDI1C9PaREJkAAJ7A0BiszeZAUTQgIkQAL1I0CRqV+e0iISIAES2BsCFJm9yQomhARIgATqR4AiU788pUUkQAIksDcEKDJ7kxVMCAmQAAnUjwBFpn55SotI4I8RcL9ZGJwY4ZdKxVc8TXQ/TDC//2NJYsR/mABF5g9nAKMngXoQ8OC8N/1Pf/tfZw0/0RwfH3Ux+VkPS2nFdgQoMtvx4tMkQAISAu7nbigwTXSvl196TX0W/HiMdZ8QlATNSxUnQJGpeAYy+STw5wk4GL7QoGk62tcSGfkxgun3bHT0p96fTy5T8KQEKiky9oUo0BoGN4KVC/tDF+Zz3b+mPWuic2FhVjQGfOfAuujAiN7RGmgedzG0ZtjwK/dPmkmMjAT2msDNIOjFvBjCkSbUw/Qs+M1qZ1NQZqSQanux0iLT/2xjYITikhkD1l/Lu+bulz4MPSzwmXeEcOmvhnCKBKq2RYGGkcBuBJz3h34DT7+wpQG4X4doPQt/c7lCJH2VF2tAoNIiE0wq6jDfTbEIm0eLSR/NsGse9HQSuZTothvnFmZ34b0HFzNrKT46W1sJaDwkgSICLiangYC0rhfpBx/msN4aGWeAHjhilsZU97OKi4xsDNiFdRIW+n+S48MuJm+CXs/huS3tsntf+zj0BaqF8a+6Zz3tI4E0gcV1KxhylvTwYy+x8N5SUBYYHwe/t2Sjzv02QifqvegG+h+HaPG3lQauyFmlRSZPLKI5Gy3ZfXcn6PqF3MDoR17uzjF6Gfxgup85O5NHidfrSeBRROZhgem7pStz4/gKjv9TsjGgyNSz4KyxqtIis2xNpa2UisztMOylDCAfOQ7CiN49fC+fwkzHxDMSUJ3AsifT/d8YvWiOVDfQu54tRwziRh5HCVQrMeqIzM0gHArYTGRSvSDVSgXtJYGNCSxgvQ56/9GQmv5qgGlmega/xuFwWb+wkbdxtHywMgTUEZn/QjdLbY3InAc/GONjcj6nMvnJhJLAkxNw3kUeng10PuUsA/jaDxp5L0dckPnkOfRnI1RHZBYW2mvnZKJFZRp6X+jN/2eLJmN/agK7zckA3pdeICB6fgPOvgiEKM/N+altZXxPR0AdkcEcIzPopeQ5DIgfiy6ESO/TzfLpyiBj2hMCu4oMvCn6/tozmbcngJ/RUNkhhrd7YiyT8WQEFBKZoMXli4gWrK2Jd4Z9cOFc98JFmjk/lCfLEkZEAtUjMP9ohnOe+XuXcf1Z9fL1MVKslMgAa3aK1XQY7+RraB4DNsMggfoSmMM6aYRCk3YE4E4a9c31TSxTTGQCJOKbF8PTFprxYrEDGCcDWN+4NmaTQsNnSEBOwMV8coXuq4Nwlb+OA6ODAfcElONS5GolRUaRvKGZJEACJFB5AhSZymchDSABEiCB/SVAkdnfvGHKSIAESKDyBCgylc9CGkACJEAC+0uAIrO/ecOUkQAJkEDlCVBkKp+FNIAESIAE9pcARWZ/84YpIwESIIHKE6DIVD4LaQAJkAAJ7C8Bisz+5g1TRgIkQAKVJ0CRqXwW0gASIAES2F8CFJn9zRumjARIgAQqT4AiU/kspAEkQAIksL8EKDL7mzdMGQmQAAlUngBFpvJZSANIgARIYH8JUGT2N2+YMhIgARKoPAGKTOWzkAaQAAmQwP4SoMjsb94wZSRAAiRQeQIUmcpnIQ0ggT0jcOdg/NYIv445gL1nyWNynpYAReZpeTM2EqgvgYcFppctNDQNWvyfIlPfDN/MMorMZpz4FAmQQC4BF/PJEK1ngbjoRh+jy1YoNBSZXGyK3KDIKJLRNJMESiPgTdHXhcDoMN/ZcAEsrikypfGuWMCVExnn8jBoIZkjzHNhzzF6GbSqzE+Sp0S3/kMXraNG2NpqoHncxdVk7v9AcoOFaLFdoXts4MD/UQVxNI4MGCdD2OLXxX8koBwBD9OLDkbflj8AioxyhSDX4MqJDH6MYPrjvYcY3ubYdTvEof9MB9Zd5pm7KfpHgTho+gGMlwaMWGw0NE6sHPGawzqJRCl8Px53FuctjH9l4uIpCShKgCKjaMZLzK6eyGCOkRlU8oeXjsQkwHkf9nZOJ5meSfSuDvO9k763mMTiY35c7f24Vifo9Rx1Mb514SVi9twFZjcOFsmLifs8JAHVCFBkVMvxfHsrKDJAXOHrsklFB8MXQoR09KfpWt/93A3cKk+stMBEfKIekCRc+yIQtub/ZtHT/EsCtSKwFIagrC89xFbPW9eLQtuXYcl+o4Wv8mbNCFRSZJCYaMwKCSKheDFEup/jYnIa/Fh6X9Lis8xTG31/CKyF8c/lVXE0/2jEPRnrR9776Xd4RgJVIrAUhlVRyQoORaZKOftn01pNkYGH6d96UOlnhsQix4DVoTQHg3Cy3p+oF3MxK/+bsY//4CaTMfc2BtFcjqahYXYxvJ5ilp3zybzGUxJQkcBSsNiTUTH/kzZXVGSAuMeiJSf37VBITIx+JM0UxzYGqYn64tbaisiIIO5nsC7aKc8y0cJrmD2ME5412Zh5TgKqEaDIqJbj+fZWV2QSDgBR192b9oM5F6l781JkpAKSz2j1zoOH+a2Fq1MzIThNDG44jLYKi1dUJECRUTHX5TZXWGQSC758UVkOoXWspb/+0uwFxsdB7yUSpeW93zjy5hi/Dofujscong79jXj4KgmUTGApDMW9fNF7X/cbWobF4bKSs23vg6+0yODOQscfAjMx+hatOu5iItOY1OT9APb9I+bNzSCYH9IHGWeDR4yDQZFAyQSWwkCRKRm1UsFXW2QSDgCmafoVvf73NLWGJZWbdxN0w8l/3ehhdDOH9xA94cH96cD61EPrMrtvrAv7swX7+wKumx4S837auAp7MoVxR9HwLwnUkIDnunAT/2cfo21l+pgkrruP2birIcc6mlRxkQFwMwi3FBetr4JdAMLc824GMBJbwmRdM8W5/i7t/Awsh9pkz/vXjvqY0tOsjr8R2rSWwAa/j8jp5iLbgFsbOB+oOIHqiwyixZcaNOmEvySH3Bmsyy5axkEsUPpzA63TK1i3slkVF/anvr9nmfE8nH/xfzTBnmfDaxuLuEckiY+XSKDWBCgytc7e3zSu+iLj2RiEK/y7n3MmY34TEl8nARIgARLYjUDFRcaDfdEMJt037cXsxolvkQAJkAAJ7ECguiJzN4N1Hn7iVW+vbAOzAwu+QgIkQAIk8MgEKiYyywWV8QS8bnAR5CMXCgZHAiRAAo9FoLIiIybqOxcWZpyGeayywHBIgARI4NEJVExkHt1+BkgCJEACJFAiAYpMiXAZNAmQAAmoToAio3oJoP0kQAIkUCIBikyJcBk0CZAACahOgCKjegmg/SRAAiRQIgGKTIlwGTQJkAAJqE6AIqN6CaD9JEACJFAiAYpMiXAZNAmQAAmoToAio3oJoP0kQAIkUCIBikyJcBk0CZAACahOgCKjegmg/SRAAiRQIgGKTIlwGTQJkAAJqE6AIqN6CaD9JEACJFAiAYpMiXAZNAmQAAmoToAio3oJoP0kQAIkUCIBikyJcBk0CZAACahOgCKjegmg/SRAAiRQIgGKTIlwGTQJkAAJqE6AIqN6CaD9JEACJFAiAYpMiXAZNAmQAAmoToAio3oJoP0kQAIkUCIBikyJcBk0CZAACahOgCKjegmg/SRAAiRQIgGKTIlwGTQJkAAJqE6AIqN6CaD9JEACJFAiAYpMiXAZNAmQAAmoToAio3oJoP0kQAIkUCIBikyJcBk0CZAACahOgCKjegmg/SRAAiRQIgGKTIlwGTQJkAAJqE6AIqN6CaD9JEACJFAiAYpMiXAZNAmQAAmoToAio3oJoP0kQAIkUCIBikyJcBk0CZAACahOgCKjegmg/SRAAiRQIgGKTIlwGTQJkAAJqE6AIqN6CaD9JEACJFAiAYpMiXAZNAmQAAmoToAio3oJoP0kQAIkUCIBikyJcBk0CZAACahOgCKjegmg/SRAAiRQIgGKTIlwGTQJkAAJqE6AIqN6CaD9JEACJFAiAYpMiXAZNAmQAAmoToAio3oJoP0kQAIkUCIBikyJcBk0CZAACahOgCKjegmg/SRAAiRQIgGKTIlwGTQJkAAJqE6AIqN6CaD9JEACJFAiAYpMiXAZNAmQAAmoToAio3oJoP0kQAIkUCIBikyJcBk0CZAACahOgCKjegmg/SRAAiRQIgGKTIlwGTQJkAAJqE6AIqN6CaD9JEACJFAiAYpMiXAZNAmQAAmoToAio3oJoP0kQAIkUCIBikyJcBk0CZAACahOgCKjegmg/SRAAiRQIgGKTIlwGTQJkAAJqE6AIqN6CaD9JEACJFAiAYpMiXAZNAmQAAmoToAio3oJoP0kQAIkUCIBikyJcBk0CZAACahOgCKjegmg/SRAAiRQIgGKTIlwGTQJkAAJqE6AIqN6CaD9JEACJFAiAYpMiXAZNAmQAAmoToAio3oJoP0kQAIkUCIBikyJcBk0CZAACahOgCKjegmg/SRAAiRQIgGKTIlwGTQJkAAJqE6AIqN6CaD9JEACJFAiAYpMiXAZNAmQAAmoToAio3oJoP0kQAIkUCIBikyJcBk0CZAACahOoNYi4056aJ+NMPnulpzPczg3C2kcC2uAgeXAfZDefvyLCwu9v652s/nOQu/NGLOycT2+1QyRBEhgTwnUWmRwM4CmdTCW1/+bZYk3g/V+iOFlwf9TE5qmw3jvrIS5uG5B05roTn4nEYlgH+YYvx3Avk9cSx3aGGgamhc2ttWK+afADvPMwuypRDGVdp6QAAnUjYACIjOAnZNr889dtC5seDn348v3Ltyih3wx62IiqfgDkclPgx/HnY3ROiELRa73SoemadCO8oQmEJnBTZz6zQ7up+jpgTgVmQrMMRU9s81C5VOPTeBhAWc6hfNIbZbHTh7DI4EsgQqLjAv7Y0HvQlTKfg/DRFfWC3lrQheVtaajfT3Pctnu3BcZuZBsJDIitqyQ/RqjpWk4vFztHRUnbheR8eC8a0LTDHQuipn2T8RzGhonY8yL1ag4mY9w174Q+aehda1KjTvHyAxs1vQ2rF+PAJFBkEDJBCosMgAePLiS3kPMrKDyj595jIOCeDYWmUw63M9daNohhreZG6nTGawPE8zukhe3FxnvvwGaehvjn8lwZMdhJae3Mfr25/syyomMN0XPbxgFQrN1b1WWpbxGAiUTqLbIrINTUPmve3Wr+wXx7CYyHqZnGrSXIxT3sQJB0V+PE89tKTL3NgZHDXSs9b2B+T9ifukRen5bwc1/WDmRgQfnfy00NB0Hf1mJPM9nxDsk8KcJVFdkflmw/luDr6DyT77pLRZr5hgWcL7M8udu/Hh6mEqGj3YSmbDFan7KSMy9g+ltMhKZoMiuJa1NHs8xft2AfnwFZ03HxLsZoKlp0E8na1glwy/3WD2RKZcnQyeBMghUVmTEcJJ5Wjx/UDgnE8/T9GCKCe83k4KWoYPhCw2N457cy8yf+2lhLBkj30VkXKsDTTtA6yxtXzDp30T3cyQ+MkGRXZMVHQ/2hYH2xxncn2O0nxnoXc/kAuL3doqcDWThl3+NIlM+Y8ZAAr9LoKIi48I60dD+N3+IR7S8zQ1a6Lgdoqkb6H2yschz2w17Ft3POc39myHM0yvYktvbi0ww76H/PTgTeRUAACAASURBVF3pOdnnGjRzmOh1LDA+1pAem99EZDzY79roWZFYAd6Xnu8IIVyfk30lRAKz0ZzN7xbH7d5Pi4yLmTVA56gReN89a6JzOc3PUxHVnQProgPjeeixpzXQPO5iaOWIbeiMoWlyJw/E9+UNDt+6hY2xiDNKp5hj0Q9gvGyh++8yP5Ykgjz2PQoT8zGaVhCHeDlKy/EY4lfifbcwOGmiETq7HLzq4uqrpMDGEYc8jYPQQSZ0OEilIVv24pd5QAIxgUqKTDR0kycy3vcR2roO4+0IdlKHVkRkgfFJZ/2E948RDPGjXjsxHnOND7YWmdshDqUVSNCbMj4mK6JdRMbF9KInmbh3MTkVlW0Xk6juuZ9h9FqHppsYpobpYvP+6EEsMv/YsE5CcclUgvpry69kswl1v/Rh6PKKU1To+qshnKxTSVRx7ygyotwWxaldyJztf1NkWiNM/+2E4pK1t4nBTapJEWISw6iR8Oo4MAwYGbFpHBkwXhq4WjdknQXPc+UIVFBkHAyfa2iYQ+mCxMWkD8PoYrzi/RTMP5jvE2s8biewNhAO39PrxRDbOhOL0rSdyAQVStPs4ipbqfvik/U2215kvF/z/Na9iOPoCjOR8Fhg2hh9l1VEf/63EomMrosKUYf5bopFmFRRDsQcktRD78cIZtiiN86tpXfeg2i9L8VHP8v0Jn9LZIJGQpTOeVLAPBfuTwfTTXamiNOwYU8mEt2jLsa3YevBDRsP4l7Y00nmZrAoVwyP9pFaQ/zTQvcoEKrmB7+UJF/jMQlICVRQZKR2+EMf47cm2tIhkjkmb5r+sET7MlGp5ASVvhwMzWnZCif9EPDdSQxjLW9uIzL+kNXREM6DqJDSrUzn8hDaitBtLzLLlMmPPFFJuzYGhg7tqLuRCMtDmmN6ITyhGjDPiua75G9vcjUSGd/j7Z9kD0+8HebbyjoaF5M3QSv98DwzNBhG6n3t49CvnDMVeVzB7zBcFr8rX7S7ib3+M3E4mbRlA4ify5lL8xstQjD6mcXKc4xeBkLS+7LauAjmCzVoraRHYzZynpPAkkAtRMa+bAbzCSeDzMR8H91jwx9zb2wyP7PkEh+JH5VYtHmQN+nvOxD00REtvGcdjH/Er/oHG4vMvY3+0XKtyvyjAU3vYuKvgbEx0DWkh8pE8I8vMghbq/5wUTRsljZps7P/BomxfB2DEoZVIpHJE4vofmoYyp2g6wuIgVEmr5aGLSva1DxcXHHvIDLxGhcd5nt7973s4jRsKjI5w7y54QRzerlzPr4npRChHAZLiDwiAZ9ALUQGP0ZomV0Mryewvy/gui48z8V8MkTrqIXhNJiY8W4tWDeL9MT22oLgwb7srWnRO4EISIYQNhOZYCI+NT7uV9JB5Ry0HmWVSjAEs/3Ef9ZoF84XG44YahRzWedTuZdZ/JqH2U2BS7d47glFJm/Fv1Rk4hZ8cSUZvXuY3I8urphz3o3vy/IKmF+3l8KrH/ibt1q3W5bHNXHEWRQ/t21ao2E9DYU9mZy5rjh+HpBASKAeIpPJTvd2jJ5pSj3G/Anf5y0M8jyIMmFtdLqw0NY09L+uPr2JyHg3V7jKTsCKMI8GcO4dDI80HGa9vvyoglZnOt5NvMsy6VxM0HsRDJFoRx0MYvfutAt1vElouCVP86xIjISDgYmGqEwvt9+sM5NC6WkkBFuJzIYt8SjsVC9o54p7mXz36xW6ZsZJwWe0xhMuCiJOg1zIosdi77K8HkdBOPOPYqPUnDmZsJzkMY/j5wEJhARqJTLujwmGx020LqzC7eq926G/NkY3+pimtmTZsVx87UPT2pAtmt9EZOBPhMjj9lfZx8Nm2WcCQUn/4LcQGW+B6WULjWcGDFF5SL2bsnFG7rE5wzCSx8u6FAlB2v5lbNH9lF1xDyunhR++7ruLa5khyrhiznk3vr9GAIRL8d0M0+uEy7XwaEvt3LC0I3W0aRzxczuk9efI3zcvcJte9S5rnHC3gVSe8KSQQPVF5sHD/GaMwbFoHRro/TPFdDrB+EPYCj/vovVSuFu20Do2YZyIBZUjWNeh99EjrGD3509WJuUD7huJTF4WiUWSetoBIP3ojiLjzjH50IEp1kpMxXBNMLeTqozTEaXP/ApsfUWafunxzyIR2Upkwl6nKCv5czI5Q0ZxxS3f3QHfr2DIHAbWmO5Og90UhANDeuhT8mKchjX84+e2FZmwLIjPU1wO0Ildl4XYdB53BEBiHi/Vj0DlRSZaRBi0uoLFdP3LK4wnU0xvx+hreQvGPNjnh5Atetwum8Mf5blsjcO2LsyJmP1FkDraK15TiWfgYHR6hemvpBdQfk/G/T7B6LyP/iexqWbynRJExpvDemtA1xpofXC2nAdL2ph/vJPIYLmTcZ7DQFym9H56q6B48l4iUMIjL3TvzZ00zzUlqtiLFxj7r8fiUZLI+GvC6D2Wm1W8sTWByouM8LCyLoaQT6DmV7g+qfsFFsn1Clvji4aONKS8kBLh7NSTEfMwrxow3sldbBPBSw5zbBY7Vid1JfVmCSITz32IuZ41FWIqLZuf7CYyy90NVtasPLhwrnvhgknZRqBLMdBfj+IhWTEHGK0fCRo7Ent/TDGeOJgLp5TkomAvWJsTrOkxC3pXIZeyRSYaTtTbuLqZ+040hTudb55dfFJRAjUQmSjnXDjvTRhvLMzjH3GywvWw+DrC4HwE63ae/qFHQaz9662857wX31dJrJLPhLG1yPhrVA7Q+bTGeysTz/LULui9LZ9KH5UgMrEXlxCZfD7pdGx3tqvIQOxm/D76nlDo8OAPc0XHeq7Ax72c1PPiPbGn3Nj3MpSKakp0o3iSf3W0P81Xe3xr3wvDyC6qjMVo2+EyB1dijdSKfVFaOWy2XSnl0/UQGbGCWWwr8kx8oGyM6Y9ogUdSZMLMfggnu/UDf7+xySarrONyErlFN/0tNYxwvLqZdHONnw0OthEZ99sInVc9jDdeYe9h9k8f3bN+vD6o/5cYosobIswkLj4NRUa4ga/zLBP3/27nbH0TByimtuF8aKEh9oWLN/RM3v/9491FJojb/WZheNpC81lYgYo9xE4GsFZ2i0in1f06XM5V+O8MEXjJRz0dWU9mguFZB8bLaP+wIE79uYHO2QiTuMym4wo+IR5V8AV/H01kgPm/HRwIkfH3VAu2jzmQbMGzss9dJuk8JQFBoOIi42J23YN51PbXwojRIPfnDAvXDbr5P8fo5FW4iykG4aeMhbdMcouztUXjYY7RsfjBi/3RilezbyQyQvje939rUjU1ZCNcn3OHxmTW7dKTkcxLyILmtUoR8Kb9YJ8z8XnvqK2WtEAMKX6M1vvIPSqTj/OYBCoqMkGPovPXAOObjDx4C9jXA7Si1qnWxNW3vIx2Mf1bDHdJWp55r4TXvV+zzOS5/IWF1UPvU2K/tJXHFrAnzu4rwJPhCdfs/xvC3tote47xXz2Mor2tkmHKjl0H9qbPyt7ntT0lIDZJDXpLq7tLJJL8M/g0+C6/m0QoPFSEQPVE5mHuV8rRRoi5+STcf5+3MfiS3dMq+4a7fvV69hWek0AtCSxFRhPbMMkaK3cOxmIfQDGcZq77cmstIdGoLQlUT2S2NJCPkwAJbEHg+8hfqBxN/Is5I7Glv/8//u6OBt3oYbLBDuZbxMxHa0qAIlPTjKVZJLAzAbFY91MPnZcGUhP+z5r+YubRZL5mb7udY+aLNSRAkalhptIkEiABEtgXAhSZfckJpoMESIAEakiAIlPDTKVJJEACJLAvBCgy+5ITTAcJkAAJ1JAARaaGmUqTSIAESGBfCFBk9iUnmA4SIAESqCEBikwNM5UmkQAJkMC+EKDI7EtOMB0kQAIkUEMCFJkaZipNIgESIIF9IUCR2ZecYDpIgARIoIYEKDI1zFSaRAIkQAL7QoAisy85wXSQAAmQQA0JUGRqmKk0iQT+FAHxtdHByXJjTf25ie6HCeb3fypFjPdPE6DI/OkcYPwkUAsCHpz3pv/p7+gzAam/R11+GqAW+by9ERSZ7ZnxDRIggQwB93M3FJgmutfLL72mPgt+PMa6TwhmguVpDQhQZGqQiTSBBP4sAQfDF+KzzTra1xIZ+TGCKb6kqenoT70/m1TG/uQEKiky9kXwHfLBjeDlwv7QhRl9te9ZE50LC7OiMeA7B9ZFB0b0jtZA87iLoTXjx5ievAgywsoTuBkEvZgXQzhSYzxMz4LfrHY2BWVGCqm2FystMv3PNgaGHnxv3G8phQVZ06C/lnfN3S99GPryudS4sXjv1RBOkUDVtijQMBLYjYDz/tD/DeoXtjQA9+sQrWfhby5XiKSv8mINCFRaZAKB0GG+m2IRNo8Wkz6aYdc86OkkcinRbTfOLczuwnsPLmbWUnx0trYS0HhIAkUEXExOAwFpXS/SDz7MYb01Ms4APXDELI2p7mcVFxnZGLAL6yQs9P8kx4ddTN4EvZ7Dc1vaZfe+9nHoC1QL4191z3raRwJpAovrlnRUINvbF+dLQVlgfBz83pKNOvfbCJ2o96Ib6H8cosXfVhq4ImeVFpk8sYjmbLRk992doOsXcgOjH3m5O8foZfCD6X528x7idRKoJYFHEZmHBabvlq7MjeMrOP5PycaAIlPLcrPOqEqLzLI1lTZTKjK3w7CXMoB85DgII3r38L18CjMdE89IQHUCy55M939j9KI5Ut1A73q2HDGIG3kcJVCtxKgjMjeDcChgM5FJ9YJUKxW0lwQ2JrCA9Tro/UfDavqrAaaZ6Rn8GofDZf3CRt7G0fLByhBQR2T+C90stTUicx78YIyPyfmcyuQnE0oCT07AeRd5eDbQ+ZSzDOBrP2jkvRxxQeaT59CfjVAdkVlYaK+dk4kWlWnofaE3/58tmoz9qQnsNicDeF96gYDo+Q04+yIQojw356e2lfE9HQF1RAZzjMygl5LnMCB+LLoQIr1PN8unK4OMaU8I7Coy8Kbo+2vPZN6eAH5GQ2WHGN7uibFMxpMRUEhkghaXLyJasLYm3hn2wYVz3QsXaeb8UJ4sSxgRCVSPwPyjGc555u9dxvVn1cvXx0ixUiIDrNkpVtNhvJOvoXkM2AyDBOpLYA7rpBEKTdoRQDgEcCeN+ub8OssUE5kAh/jmxfC0hWa8WOwAxskA1jeujVlXYHifBPIJuJhPrtB9dRCu8tdxYHQw4J6A+cgUuFNJkVEgX2giCZAACdSCAEWmFtlII0iABEhgPwlQZPYzX5gqEiABEqgFAYpMLbKRRpAACZDAfhKgyOxnvjBVJEACJFALAhSZWmQjjSABEiCB/SRAkdnPfGGqSIAESKAWBCgytchGGkECJEAC+0mAIrOf+cJUkQAJkEAtCFBkapGNNIIESIAE9pMARWY/84WpIgESIIFaEKDI1CIbaQQJkAAJ7CcBisx+5gtTRQIkQAK1IECRqUU20ggSIAES2E8CFJn9zBemigRIgARqQYAiU4tspBEkQAIksJ8EKDL7mS9MFQmQAAnUggBFphbZSCNIYI8I3DkYvzXCr2MOYO9R0piUpydAkXl65oyRBOpJ4GGB6WULDU2DFv+nyNQzsze3iiKzOSs+SQIkICXgYj4ZovUsEBfd6GN02QqFhiIjRabQRYqMQplNU0mgFALeFH1dCIwO850NF8DimiJTCusKBlo5kXEuD4MWkjnCPBf4HKOXQavK/CR5SnTrP3TROmqEra0GmsddXE3m/g8kN1iIFtsVuscGDvwfVRBH48iAcTKELX5d/EcCyhHwML3oYPRt+QOgyChXCHINrpzI4McIpj/ee4jhbY5dt0Mc+s90YN1lnrmbon8UiIOmH8B4acCIxUZD48TKEa85rJNIlML343Fncd7C+FcmLp6SgKIEKDKKZrzE7OqJDOYYmUElf3jpSEwCnPdhb+d0kumZRO/qMN876XuLSSw+5sfV3o9rdYJez1EX41sXXiJmz11gduNgkbyYuM9DElCNAEVGtRzPt7eCIgPEFb4um1R0MHwhREhHf5qu9d3P3cCt8sRKC0zEJ+oBScK1LwJha/5vFj3NvyRQKwJLYQjK+tJDbPW8db0otH0Zluw3Wvgqb9aMQCVFBomJxqyQIBKKF0Ok+zkuJqfBj6X3JS0+yzy10feHwFoY/1xeFUfzj0bck7F+5L2ffodnJFAlAkthWBWVrOBQZKqUs382rdUUGXiY/q0HlX5mSCxyDFgdSnMwCCfr/Yl6MRez8r8Z+/gPbjIZc29jEM3laBoaZhfD6ylm2TmfzGs8JQEVCSwFiz0ZFfM/aXNFRQaIeyxacnLfDoXExOhH0kxxbGOQmqgvbq2tiIwI4n4G66Kd8iwTLbyG2cM44VmTjZnnJKAaAYqMajmeb291RSbhABB13b1pP5hzkbo3L0VGKiD5jFbvPHiY31q4OjUTgtPE4IbDaKuweEVFAhQZFXNdbnOFRSax4MsXleUQWsda+usvzV5gfBz0XiJRWt77jSNvjvHrcOjueIzi6dDfiIevkkDJBJbCUNzLF733db+hZVgcLis52/Y++EqLDO4sdPwhMBOjb9Gq4y4mMo1JTd4PYN8/Yt7cDIL5IX2QcTZ4xDgYFAmUTGApDBSZklErFXy1RSbhAGCapl/R639PU2tYUrl5N0E3nPzXjR5GN3N4D9ETHtyfDqxPPbQus/vGurA/W7C/L+C66SEx76eNq7AnUxh3FA3/kkANCXiuCzfxf/Yx2lamj0niuvuYjbsacqyjSRUXGQA3g3BLcdH6KtgFIMw972YAI7ElTNY1U5zr79LOz8ByqE32vH/tqI8pPc3q+BuhTWsJbPD7iJxuLrINuLWB84GKE6i+yCBafKlBk074S3LIncG67KJlHMQCpT830Dq9gnUrm1VxYX/q+3uWGc/D+Rf/RxPseTa8trGIe0SS+HiJBGpNgCJT6+z9TeOqLzKejUG4wr/7OWcy5jch8XUSIAESIIHdCFRcZDzYF81g0n3TXsxunPgWCZAACZDADgSqKzJ3M1jn4Sde9fbKNjA7sOArJEACJEACj0ygYiKzXFAZT8DrBhdBPnKhYHAkQAIk8FgEKisyYqK+c2FhxmmYxyoLDIcESIAEHp1AxUTm0e1ngCRAAiRAAiUSoMiUCJdBkwAJkIDqBCgyqpcA2k8CJEACJRKgyJQIl0GTAAmQgOoEKDKqlwDaTwIkQAIlEqDIlAiXQZMACZCA6gQoMqqXANpPAiRAAiUSoMiUCJdBkwAJkIDqBCgyqpcA2k8CJEACJRKgyJQIl0GTAAmQgOoEKDKqlwDaTwIkQAIlEqDIlAiXQZMACZCA6gQoMqqXANpPAiRAAiUSoMiUCJdBkwAJkIDqBCgyqpcA2k8CJEACJRKgyJQIl0GTAAmQgOoEKDKqlwDaTwIkQAIlEqDIlAiXQZMACZCA6gQoMqqXANpPAiRAAiUSoMiUCJdBkwAJkIDqBCgyqpcA2k8CJEACJRKgyJQIl0GTAAmQgOoEKDKqlwDaTwIkQAIlEqDIlAiXQZMACZCA6gQoMqqXANpPAiRAAiUSoMiUCJdBkwAJkIDqBCgyqpcA2k8CJEACJRKgyJQIl0GTAAmQgOoEKDKqlwDaTwIkQAIlEqDIlAiXQZMACZCA6gQoMqqXANpPAiRAAiUSoMiUCJdBkwAJkIDqBCgyqpcA2k8CJEACJRKgyJQIl0GTAAmQgOoEKDKqlwDaTwIkQAIlEqDIlAiXQZMACZCA6gQoMqqXANpPAiRAAiUSoMiUCJdBkwAJkIDqBCgyqpcA2k8CJEACJRKgyJQIl0GTAAmQgOoEKDKqlwDaTwIkQAIlEqDIlAiXQZMACZCA6gQoMqqXANpPAiRAAiUSoMiUCJdBkwAJkIDqBCgyqpcA2k8CJEACJRKgyJQIl0GTAAmQgOoEKDKqlwDaTwIkQAIlEqDIlAiXQZMACZCA6gQoMqqXANpPAiRAAiUSoMiUCJdBkwAJkIDqBCgyqpcA2k8CJEACJRKgyJQIl0GTAAmQgOoEKDKqlwDaTwIkQAIlEqDIlAiXQZMACZCA6gQoMqqXANpPAiRAAiUSoMiUCJdBkwAJkIDqBCgyqpcA2k8CJEACJRKgyJQIl0GTAAmQgOoEKDKqlwDaTwIkQAIlEqDIlAiXQZMACZCA6gQoMqqXANpPAiRAAiUSoMiUCJdBkwAJkIDqBCgyqpcA2k8CJEACJRKgyJQIl0GTAAmQgOoEKDKqlwDaTwIkQAIlEqDIlAiXQZMACZCA6gQoMqqXANpPAiRAAiUSoMiUCJdBkwAJkIDqBCgyqpcA2k8CJEACJRKgyJQIl0GTAAmQgOoEKDKqlwDaTwIkQAIlEqDIlAiXQZMACZCA6gQoMqqXANpPAiRAAiUSoMiUCJdBkwAJkIDqBCgyqpcA2k8CJEACJRKgyJQIl0GTAAmQgOoEai0y7qSH9tkIk+9uyfk8h3OzkMaxsAYYWA7cB+ntx7+4sND762o3m+8s9N6MMSsb1+NbzRBJgAT2lECtRQY3A2haB2N5/b9ZlngzWO+HGF4W/D81oWk6jPfOSpiL6xY0rYnu5HcSkQj2YY7x2wHs+8S11KGNgaaheWFjW62YfwrsMM8szJ5KFFNp5wkJkEDdCCggMgPYObk2/9xF68KGl3M/vnzvwi16yBezLiaSij8Qmfw0+HHc2RitE7JQ5HqvdGiaBu0oT2gCkRncxKnf7OB+ip4eiFORqcAcU9Ez2yxUPkUCJKA4gQqLjAv7Y0HvQlTKfg/DRFfWC3lrQheVtaajfT3/vWLgi4xcSDYSGRF7Vsh+jdHSNBxervaOihO7i8h4cN41oWkGOhfFTPsn4jkNjZMx5sVqVJzMR7kb2OqLrp+XIj/Ff3lePEqUDIQESGArAhUWGQAPHlxJ7yEmUFD5x888xkFBPBuLTCYd7ucuNO0Qw9vMjdTpDNaHCWZ3yYvbi4z33wBNvY3xz2Q4suM5RqYGTW9j9G0f+jIOrl4aMKL/Rw2KjCzbeI0E/iCBaovMOnAFlf+6V7e6XxDPbiLjYXqmQXs5QnEfKxAU/fU48dyWInNvY3DUQMdaP2c0/0fMLz1Cz28ruFs87OcDezJbEOOjJFA6geqKzC8L1n9r+BRU/sk3vcVizRzDAs6XWf7cjR9PD1PJ8NFOIuNN0dM0mJ8yEnPvYHqbjEQmKLJrSWuTx3OMXzegH1/BWdMx8W4GaGoa9NPJGlbJ8J/4mCLzxMAZHQmsJ1BZkRHDSeZp8fxB4ZxMPE/TgykmvN9MEr2BLDgHwxcaGsc9uZeZP/fTwvhX9j1gF5FxrQ407QCts7R9waR/E93PkfjIBEV2bTVdgAf7wkD74wzuzzHazwz0rmdyAfF7O0XOBrLw/8A1iswfgM4oSaCYQEVFxoV1oqH9b/4Qj2h5mxu00HE7RFM30PtkY5Hnthv2LLqfc5r7N0OYp1ewJbe3F5lg3kP/e7rSc7LPNWjmMNHrWGB8rCHtSbaJyHiw37XRsyKxArwvPd8RQrg+J/tKiARmozmb4sJW+t1tRebOgXXRgfE89NjTGmgedzG0csTWN8DD4tbC6KwDI54D0tA4Ek4TVu4aI/sicEoI8sqF/aELM4r3WTN4t2h+sXR4jIAEyiFQSZGJhm7yRMb7PkJb12G8HcFO6tCKiCwwPumsn/D+MYKhtdY/J8mjrUXmdohDEddKryjoTRkfl8IA7CIyLqYXPcnEvYvJqahsu5hEYnk/w+i1Dk03MUwN00kM3YdLW4iM+6UPQ4+80Vb/6q+GcCSVfpCfq8/HHm45YhyJTP+zjYERiVo6nPTc2j4AZRpI4PcJVFBkHAyfa2iYQ+mCxMWkD8PoYrzi/RTMP5jvE2s8biew1npUAb6n14shtnUmFtmzncgEotE0u7jKVuq++GS9zbYXGe/XPL/HJuI4usJMJDwWmDZG31N9m98vdWWFsKnI/BjBDN3XjXNr6Z334GJmLcVHP1vtTS7+7aB9Mcbkdp5aO+X9nKB/FIiG/mZ13ioSmUCMdJjvpliEWEWZFfNdwqki3SstCxTDJYGnI1BBkcmBc+dg/NZE+3IqqUTnmLxpQtMP0L5MVCo5QaUvB0NzmqTCST333UkMYy3vbCMy/pDV0RDOg+i1NDG4WVbuzuUhtBWh215klimTH3kiSjdsbR91NxJheUhzTC9aaGgNmGdF813yt3e6upHIuJi8CXoSh+eZocEwUu9rH4d+pS/rURakzG8ICLFYXaezFBmZd15YxjQNrX+SPdWCuHiLBCpCoBYiY182g/mEk0FmYr6P7rHhj7k3NpmfkWSamIQXizYP8ib9fQeCPjqiFfusg/GPdCAbi8y9jf7Rcq3K/KMBTe9i4q+BsTHQNaSHykQ8jy8y+Gmhe6TBHy6Khs3SJm129t8gXOwattDXeQJuFmrxU5uIjDtB1xcQA6NMXi0Dn2P0MuiV5M7DLR9eHoULaItEJk/YYhG6yNufYhkNj0igSgRqITL4MULL7GJ4PYH9fQHXdeF5LuaTIVpHLQynwcSMd2vBulmkJ7bX5pYH+7K3pkXvBCLwwR9oSoW4mcgEE/HJngv8SlrH4D8g8DaTtaqDeZr0EMsmE/+pJIquC5wvNhwx1Cjmss6nci+z+DUPs5sCl27x3L6KTEFvIzYPQFTpH0r2o8PDAo41wlBM/kcLQcVf4yAU1vyeTOs6OUm4jDGKT6PILKHwqBYE6iEymaxwb8fomabUY8yf8H3ewqDQgygT4LrThYW2pqH/dfXBTUTGu7nCVWJozA9FhHk0gHPvYHik4TDr9eU/FAhKOt4dRGYxQe9F0HLXjjoYxO7daRfqeJPQcEue5lmRGAkHAxMNf4hy+806V0lucGWTnswmzyREJlvpe7dD3+U9nuj3e0Uhu/iYIrNBbvERRQjUSmTcHxMMj5toFbiSinyNKgrd6GOa2pJlx1z/2oemtSFbNL+JyMCfCJHHwBjxiQAAIABJREFU7a+yj4fNss8EgpJuHW8hMt4C08sWGs8MGEJkNm1F+8NCu3nbZS141PNNBCTuYa0KQTItvru4lhmi9Kbohx5pzTdjOHfLOTP/3Q2Gy9J5tYyRPZklCx7Vi0D1RebBw/xmjMGx2LfKQO+fKabTCcYfwlb4eRctf0ijhdaxCeNELKgcwboOPXoeYQW7P3+yMikfFJSNRCavTIlFknraASD96I4i484x+dCB+aqLq6kYPgzmdrYWmRU363TqnvxsE5EJe52irOTPyQTDkKK30vuyFBLhmOH3YHLyGhSZJ89yRrj/BCovMtEiwmD4IlhM17+8wngyxfR2jL6WXawYZYoH+/wQskWP0ROb/Q0r6HP5hO3OIuMvgtTRLvQ2cjA6vcL017IiBPJ7Mu73CUbnffQ/iU01k++UIDLeHNZbA7rWQOuDs+U82GbkV57aRGQQbvIpdrjO8y4LF6Zqej+1VVCQl3l7yrlw3kc7e6/2kqKeCnsyK7nGCzUnUHmRER5W1sUQ1q1sQj+/wvXz9X6BhWTB3VZ5HrZe87yQdhIZMQ/zqgHjndzFtjh9OTaLHauTupIKpASRiSt8MV8hc1pIJeBxTuI4Vyv5ZATLhkmwXmUelYEHF851L1ykKXE1vok85proT6Ly5mFxM0IvtcByNX6KTDIHeKwSgRqITJRdQUvSeGNhHq/sT1a4HhZfRxicj2DdzuHFz0Tvb/LXW3nPeS++r5JYJZ8JZmuR8deoHKDzaY33Viae5ald0HtbPpU+KkFkYi8uITL5fNLp2O4s7lnEE+7ZCfjwfGWuyUv0OmTv6DkCLxb0ylfr+19GPe+j46eFIrNdTvLpOhOoh8i4M4xOGtCeiQ+UjTH9ES3wSIpMmI0P4WS3fuDvNzb5Hj27STZHbtHNwHU1dFltytxcw+C2ERn32widVz2MN15h72H2Tx/ds368Pqj/lxiiyhsizLMxFBnhBr7Os0zc/7uds/VNMnwPzocWGmJfuHhDz+T93z/eXWSCuN1vFoanLTSfhUKjH8A4GcBa2S0ikVa//CT2O/PL0TB8JyhvRetkOFyWYMlDJQhUXGRczK57MI/a/loYMRrk/pxh4br+Whmxu7BoWabXkYT5uphiEH7KuHFiQb56IacMPMwxOhYVk9gfrXg1+0YiIyqu9/3fcqsWbttiEaU/NyVcn3OHxmQ27dKTKZo4l8XBayRAAioSqKjIBD2Kzl8DjG8y8uAtYF8P0Ipap1oTV9/ystbF9G8x3LX9nIH3a5aZPJfHsbB66H1K7Je28tgC9sSBu9PwXSYwsYbj/4awt3bLnmP8Vw+j2w17da4De9NnM0nkKQmQgFoEqicyD3O/Uo42F8zNLuH++7yNwZd1e0G561ev50bCGyRAAiRAAkUEqicyRdbwHgmQAAmQwF4RoMjsVXYwMSRAAiRQLwIUmXrlJ60hARIggb0iQJHZq+xgYkiABEigXgQoMvXKT1pDAiRAAntFgCKzV9nBxJAACZBAvQhQZOqVn7SGBEiABPaKAEVmr7KDiSEBEiCBehGgyNQrP2kNCZAACewVAYrMXmUHE0MCJEAC9SJAkalXftIaEiABEtgrAhSZvcoOJoYESIAE6kWAIlOv/KQ1JEACJLBXBCgye5UdTAwJkAAJ1IsARaZe+UlrSOCPEhBfGx2cGDjQgw/o6c9NdD9MML//o8li5H+QAEXmD8Jn1CRQHwIenPem/+lv/+usWviV1ujvUReTn/WxlpZsToAiszkrPkkCJJBDwP3cDQWmie718kuvqc+CH4+x7hOCOcHzcoUJUGQqnHlMOgnsBwEHwxei56KjfS2RkR8jmH6PRkd/6u1HkpmKJyNQSZGxL4Ku+OBGcHJhf+jCfK7D76Y/a6JzYWFWNAZ858C66MCI3tEaaB53MbRm2PAr90+WQYyIBPaewM0g6MW8GMKRJtbD9CwcPjubgjIjhVTbi5UWmf5nGwMjFJdo7Df8q7+Wd83dL30Y4aSkbOxYfzWEUyRQtS0KNIwEdiPgvD/0G3j6hS0NwP06ROtZKDK5QiR9lRdrQKDSIhOIhA7z3RSLsHm0mPTRDLvmQU8nkUuJbrtxbmF2F957cDGzluKjs7WVgMZDEigi4GJyGghI63qRfvBhDuutkXEG6IEjZmlMdT+ruMjIxoBdWCdhof8nOT7sYvIm6PUcntvSLrv3tY9DX6BaGP+qe9bTPhJIE1hct4Ih58yogKzHvxSUBcbHwe8t2ahzv43QiXovuoH+xyFa/G2lgStyVmmRyROLaM5GS3bf3Qm6fiE3MPqRl7tzjF4GP5juZ87O5FHi9XoSeBSReVhg+m7pytw4voLj/5RsDCgy9Sw4a6yqtMgsW1NpK6UiczsMeykDyEeOgzCidw/fy6cw0zHxjARUJ7DsyXT/N0YvmiPVDfSuZ8sRg7iRx1EC1UqMOiJzMwiHAjYTmVQvSLVSQXtJYGMCC1ivg95/NKymvxpgmpmewa9xOFzWL2zkbRwtH6wMAXVE5r/QzVJbIzLnwQ/G+Jicz6lMfjKhJPDkBJx3kYdnA51POcsAvvaDRt7LERdkPnkO/dkI1RGZhYX22jmZaFGZht4XevP/2aLJ2J+awG5zMoD3pRcIiJ7fgLMvAiHKc3N+alsZ39MRUEdkMMfIDHopeQ4D4seiCyHS+3SzfLoyyJj2hMCuIgNvir6/9kzm7QngZzRUdojh7Z4Yy2Q8GQGFRCZocfkiogVra+KdYR9cONe9cJFmzg/lybKEEZFA9QjMP5rhnGf+3mVcf1a9fH2MFCslMsCanWI1HcY7+Rqax4DNMEigvgTmsE4aodCkHQGEQwB30qhvzq+zTDGRCXCIb14MT1toxovFDmCcDGB949qYdQWG90kgn4CL+eQK3VcH4Sp/HQdGBwPuCZiPTIE7lRQZBfKFJpIACZBALQhQZGqRjTSCBEiABPaTAEVmP/OFqSIBEiCBWhCgyNQiG2kECZAACewnAYrMfuYLU0UCJEACtSBAkalFNtIIEiABEthPAhSZ/cwXpooESIAEakGAIlOLbKQRJEACJLCfBCgy+5kvTBUJkAAJ1IIARaYW2UgjSIAESGA/CVBk9jNfmCoSIAESqAUBikwtspFGkAAJkMB+EqDI7Ge+MFUkQAIkUAsCFJlaZCONIAESIIH9JECR2c98YapIgARIoBYEKDK1yEYaQQIkQAL7SYAis5/5wlSRAAmQQC0IUGRqkY00ggT2iMCdg/FbI/w65gD2HiWNSXl6AhSZp2fOGEmgngQeFphettDQNGjxf4pMPTN7c6soMpuz4pMkQAJSAi7mkyFazwJx0Y0+RpetUGgoMlJkCl2kyCiU2TSVBEoh4E3R14XA6DDf2XABLK4pMqWwrmCglRMZ5/IwaCGZI8xzgc8xehm0qsxPkqdEt/5DF62jRtjaaqB53MXVZO7/QHKDhWixXaF7bODA/1EFcTSODBgnQ9ji18V/JKAcAQ/Tiw5G35Y/AIqMcoUg1+DKiQx+jGD6472HGN7m2HU7xKH/TAfWXeaZuyn6R4E4aPoBjJcGjFhsNDROrBzxmsM6iUQpfD8edxbnLYx/ZeLiKQkoSoAio2jGS8yunshgjpEZVPKHl47EJMB5H/Z2TieZnkn0rg7zvZO+t5jE4mN+XO39uFYn6PUcdTG+deElYvbcBWY3DhbJi4n7PCQB1QhQZFTL8Xx7KygyQFzh67JJRQfDF0KEdPSn6Vrf/dwN3CpPrLTARHyiHpAkXPsiELbm/2bR0/xLArUisBSGoKwvPcRWz1vXi0Lbl2HJfqOFr/JmzQhUUmSQmGjMCgkioXgxRLqf42JyGvxYel/S4rPMUxt9fwishfHP5VVxNP9oxD0Z60fe++l3eEYCVSKwFIZVUckKDkWmSjn7Z9NaTZGBh+nfelDpZ4bEIseA1aE0B4Nwst6fqBdzMSv/m7GP/+AmkzH3NgbRXI6moWF2MbyeYpad88m8xlMSUJHAUrDYk1Ex/5M2V1RkgLjHoiUn9+1QSEyMfiTNFMc2BqmJ+uLW2orIiCDuZ7Au2inPMtHCa5g9jBOeNdmYeU4CqhGgyKiW4/n2VldkEg4AUdfdm/aDORepe/NSZKQCks9o9c6Dh/mthatTMyE4TQxuOIy2CotXVCRAkVEx1+U2V1hkEgu+fFFZDqF1rKW//tLsBcbHQe8lEqXlvd848uYYvw6H7o7HKJ4O/Y14+CoJlExgKQzFvXzRe1/3G1qGxeGykrNt74OvtMjgzkLHHwIzMfoWrTruYiLTmNTk/QD2/SPmzc0gmB/SBxlng0eMg0GRQMkElsJAkSkZtVLBV1tkEg4Apmn6Fb3+9zS1hiWVm3cTdMPJf93oYXQzh/cQPeHB/enA+tRD6zK7b6wL+7MF+/sCrpseEvN+2rgKezKFcUfR8C8J1JCA57pwE/9nH6NtZfqYJK67j9m4qyHHOppUcZEBcDMItxQXra+CXQDC3PNuBjASW8JkXTPFuf4u7fwMLIfaZM/71476mNLTrI6/Edq0lsAGv4/I6eYi24BbGzgfqDiB6osMosWXGjTphL8kh9wZrMsuWsZBLFD6cwOt0ytYt7JZFRf2p76/Z5nxPJx/8X80wZ5nw2sbi7hHJImPl0ig1gQoMrXO3t80rvoi49kYhCv8u59zJmN+ExJfJwESIAES2I1AxUXGg33RDCbdN+3F7MaJb5EACZAACexAoLoiczeDdR5+4lVvr2wDswMLvkICJEACJPDIBComMssFlfEEvG5wEeQjFwoGRwIkQAKPRaCyIiMm6jsXFmachnmsssBwSIAESODRCVRMZB7dfgZIAiRAAiRQIgGKTIlwGTQJkAAJqE6AIqN6CaD9JEACJFAiAYpMiXAZNAmQAAmoToAio3oJoP0kQAIkUCIBikyJcBk0CZAACahOgCKjegmg/SRAAiRQIgGKTIlwGTQJkAAJqE6AIqN6CaD9JEACJFAiAYpMiXAZNAmQAAmoToAio3oJoP0kQAIkUCIBikyJcBk0CZAACahOgCKjegmg/SRAAiRQIgGKTIlwGTQJkAAJqE6AIqN6CaD9JEACJFAiAYpMiXAZNAmQAAmoToAio3oJoP0kQAIkUCIBikyJcBk0CZAACahOgCKjegmg/SRAAiRQIgGKTIlwGTQJkAAJqE6AIqN6CaD9JEACJFAiAYpMiXAZNAmQAAmoToAio3oJoP0kQAIkUCIBikyJcBk0CZAACahOgCKjegmg/SRAAiRQIgGKTIlwGTQJkAAJqE6AIqN6CaD9JEACJFAiAYpMiXAZNAmQAAmoToAio3oJoP0kQAIkUCIBikyJcBk0CZAACahOgCKjegmg/SRAAiRQIgGKTIlwGTQJkAAJqE6AIqN6CaD9JEACJFAiAYpMiXAZNAmQAAmoToAio3oJoP0kQAIkUCIBikyJcBk0CZAACahOgCKjegmg/SRAAiRQIgGKTIlwGTQJkAAJqE6AIqN6CaD9JEACJFAiAYpMiXAZNAmQAAmoToAio3oJoP0kQAIkUCIBikyJcBk0CZAACahOgCKjegmg/SRAAiRQIgGKTIlwGTQJkAAJqE6AIqN6CaD9JEACJFAiAYpMiXAZNAmQAAmoToAio3oJoP0kQAIkUCIBikyJcBk0CZAACahOgCKjegmg/SRAAiRQIgGKTIlwGTQJkAAJqE6AIqN6CaD9JEACJFAiAYpMiXAZNAmQAAmoToAio3oJoP0kQAIkUCIBikyJcBk0CZAACahOgCKjegmg/SRAAiRQIgGKTIlwGTQJkAAJqE6AIqN6CaD9JEACJFAiAYpMiXAZNAmQAAmoToAio3oJoP0kQAIkUCIBikyJcBk0CZAACahOgCKjegmg/SRAAiRQIgGKTIlwGTQJkAAJqE6AIqN6CaD9JEACJFAiAYpMiXAZNAmQAAmoToAio3oJoP0kQAIkUCIBikyJcBk0CZAACahOgCKjegmg/SRAAiRQIgGKTIlwGTQJkAAJqE6AIqN6CaD9JEACJFAiAYpMiXAZNAmQAAmoToAio3oJoP0kQAIkUCIBikyJcBk0CZAACahOgCKjegmg/SRAAiRQIgGKTIlwGTQJkAAJqE6AIqN6CaD9JEACJFAiAYpMiXAZNAmQAAmoTqDWIuNOemifjTD57pacz3M4NwtpHAtrgIHlwH2Q3n78iwsLvb+udrP5zkLvzRizsnE9vtUMkQRIYE8J1FpkcDOApnUwltf/m2WJN4P1fojhZcH/UxOapsN476yEubhuQdOa6E5+JxGJYB/mGL8dwL5PXEsd2hhoGpoXNrbVivmnwA7zzMLsqUQxlXaekAAJ1I2AAiIzgJ2Ta/PPXbQubHg59+PL9y7cood8MetiIqn4A5HJT4Mfx52N0TohC0Wu90qHpmnQjvKEJhCZwU2c+s0O7qfo6YE4FZkKzDEVPbPNQuVTJEACihOosMi4sD8W9C5Epez3MEx0Zb2QtyZ0UVlrOtrX898rBr7IyIVkI5ERsWeF7NcYLU3D4eVq76g4sbuIjAfnXROaZqBzUcy0fyKe09A4GWNerEbFyeRdEiABJQhUWGQAPHhwJb2HOOcKKv/4mcc4KIhnY5HJpMP93IWmHWJ4m7mROp3B+jDB7C55cXuR8f4boKm3Mf6ZDEd2PMfI1KDpbYy+sS8jI7T2mui1nnVg/GXhkQZQ10a56wPuzQi9EwOdf/c9pbtayPeegkC1RWYdoYLKf92rW90viGc3kfEwPdOgvRyhuI8VCIr+epx4bkuRubcxOGqgY62vSOb/iPmlR+j5bQW3Zg/7ZUWDdjzee5GxL0RPX0Pren3ZqFku0ZxHJFBdkfllwfpvDYmCyj/5prdYrJljWMD5Msufu/Hj6WEqGT7aSWS8KXqaBvNTRmLuHUxvk5HIBEV2LWlt8niO8esG9OMrOGs6Jt7NAE1Ng346WcMqGT6PVwhQZFaQ8EK9CVRWZMRwknlaPH9QOCcTz9P0YIoJ7zeTRG8gm+kOhi80NI57ci8zf+6nhfGv7HvALiLjWh1o2gFaZ2n7gkn/JrqfI/GRCYrs2mq6AA/2hYH2xxncn2O0nxnoXc/kAuL3doqcDWTh85qUAEVGioUX60ugoiLjwjrR0C4YKxYtb3ODFjpuh2jqBnqfbCzy3HbDnkX3c05z/2YI8/QKtuT29iITzHvof09Xek72uQbNHCZ6HQuMjzWkPck2ERkP9rs2elYkVoD3pec7QgjX52RfCZHAbDRn8wd/KAsb44sOjOeh953WQPO4i6vJXC6cIql3DizJO0MrR2xDZ4xoqMv7bmFw0kQjdCA5eNXF1ddsIQjyyPcI9J8LhqByzy8kvpDeAo4VzI80n0XvN9B82cEgL62prHAxn1yhexylVYP+XDh5jGEnR8Ii+zZJp5Ytd6kIeUICMYFKikw0dJMnMt73Edq6DuPtKP0jWhGRBcYnnfUT3j9GMLTW+udirMuDrUXmdohDEddKryjoTRkfl8IA7CIyLqYXPcnEvYvJqaigu5hE9eT9DKPXOjTdxDA1TLe0788feZh96oQVfVQBp/+mRThIsfulD0NPP5es+PVXQzhZp5KoEm6NMP03L84mBjdJmf5dkVn/fnpOLpMjd1P0jUh4JfYm54Yi+ygyGYg8/R0CFRQZB8PnGhrmULogcTHpwzC6GK94PwXzD+b7xBqP2wmstR5VgO/p9WKIbZ2JRcZsJzJBhdI0u7jKVuq++GS9zbYXGe/XPL/HJuI4usJMJDwWmDZG35OV5u8Ut8d/V+RN5IpuvB3DuVum1VvMMLlsY5idu/sxghn2Poxza+md9+BiZi3FRz/L9CazlfBRF+PbUJHdUJBFuMmKO2vy1sNlC1h/tTG4nsD56S57mQ8e5pO+P08mnDG6ccsgGaGD4VEoLM9aGE7n8KKGludiLrzHzvK93Djxn2TJ410JVFBkcky9czB+a6J9OZVUonNM3jSh6QdoXyYqlZyg0peDoTktW+GkHwK+O4lhrOXNbUTGH7I6GsJ5EL2WdIvYuTyEtiJ024vMMmXyI0/U0a6NgWj9HnU3EmF5SHNML1poaA2YZ0XzXfK3N7rqTdEPeyMrw3y5AbiYvAla9ofnmaHB8B3vax+HvghlepRJkZEthvUbAqJS7+cuAA52oVgjRLlpX73hlwuRVskwW7CDQ+Byvt49fTVsiswqE17ZnkAtRMa+bAbzCSeDzMR8H91jwx+nb2wyPyPhJybhRUv5IG/S33cg6KMjWozPOhj/SAeyscjc2+gfLdeqzD8a0PQuJv4aGBsDXUN6qEzE8/gig58Wukca/OGiaNgsbdJmZ/8Nwh6GqHR1DLK9ic1CKXxKiLI/xKX3pZ590pfdCbq+gBgYZfJq+fwco5dBDyA1DxeLTM7QafL+ynBnGPrWPZllqmRHQfmSiczShhUvRVlAkmsUGQkUXtqaQC1EBj9GaJldDK8nsL8v4LouPDEcMBmidSSGCYLZTe/WgnWzWA45bITLg33ZW9OidwIR+OAPNKVC3Uxkgon41Fi+X0kHlXPgbZZpVfuxBPM06TmHTSb+U0kUXRc4X2w4YqhRzGWdT/Mny/1XPcxuCly6xTNPIDLO+8NAZNb1MpPmxr0N+Q4N0aNRBXuY3I8uFpGcd+P7srwKQ95VZBYOrE9Df3Gk8dJA/D9ydMj2ZDYS08ha+d+IAdfJyPnw6mYE6iEyGVvd2zF6pin1GPMnfJ+3NvTKyQScd7qw0NY09L+uPrCJyHg3V7hKTRaLToqF9tEAzn0wrn6Y9fryowoEJR3vDiKzmKD3Ihy7P+pgELt3p12o401Cwy15mmdFYiQcDEw0/CHK7TfrXCW5eiWqBGVDRatPh1eiSl7LEYrwMWnYsYjkvBvff0yR8eC8j7ZACvPI74lljrMis0laciEFNyIGFJk1oHi7kECtRMb9McHwuInWhVW4Xb13O/TXxuhGH9PUliyFrPJvfu1D09qQLZrfRGTgT4TIg/dX2cfDZtlnAkFJVwJbiIy3wPSyhcYzA4YQmWxFlY0uOvcrsJwho+iZJ/gbVYLaucTtNy/+uIeVIxThe767uJYZoowr7px34/uPJzLetB8OOzbRvXZWNmrNHS5LpmUD5xYZrohvunzJnuQ1EsgnUH2REV42N2MMjhv+Bo+9f6aYTicYfwhb4eddtPzhhRZaxyaME7GgcgTrOvTMeYQV7P78ycqkfAB9I5HJyx+xSFJPOwCkH91RZNw5Jh86MMW6jqkYPgzmdrYWmbx5h3QiSztb/NsOhsty2EsjDnudYjPQ/DmZYBhSzPf0viy91RBX3I8gMmu3DBKpD7cXKtgoNVdkEAzhChs61m6Ta5HIrM4FSsnyIglICVReZKJFhMEah2ABXv/yCuPJFNPbMfq5i8Y82OeHkC16lJLKvRhW0Dmt6Z1Fxl8EqaP9T3JdTDYRDkanV5j+SlSEyO/JuN8nGJ330f8kNtVMvlOCyHhzWG8N6FoDrQ/OlvNgWTtzzhOuyJvvpB1u8ikq7jzvsnBhqpZ1KHgMkfHXXImhrg6stb3oMF+yPaoIh+tgGH36YaUX6mH6d7g+RuYJF4VR8NdvPImhuRNrzRxdQSC8pTyByouM8LCyLoawbmUT+vkVrp/z9wsssgvuti0SYcWT8kJKhLGTyIh5mFcNGO/kLraJ4CWHOTaLHauTupJ6swSRiec+RIVaMHyUSse2J6KlHy00bKB1OcU8YWTeOpllw0SH+W6KeVQGHlw4171wkaZkI9DHEBnRCAjdrvXXo9S6Hpn19kUkFH1MosaEt4D9KUpnODezIjKAcIgJ1gNp0I0exuI3ssU6GeFuHa1Ban9cHaqTpZfXSCBLoAYiE5nk+hOkxhsL8+iHlGrVe1h8HWFwPoJ1m1iUFr2+0V9v+SMNn3fei++rJFbJZ8LZWmT8NSoH6Hxa472ViWd5ahf03pZPpY9KEJnYi0tUgvl80unY4UwsGj0RQ6VhZSv5m/a+E3Gsm0zX5QL/KCIDzK/bCffuTLqzYuEPmWaeiWzUDfT/Fvvc5c+nrdvZoHDhKMQC5kjEV9OwynWH/OMrtSdQD5ERq61FRfNMfKBsjOmPaAxa0qp/CCe79QN/v7HJ9+jZTfI6cotuBi6kxoFfWTSTbq6ZYLYRGffbCJ1XPYw3XmHvYfZPH92zfrw+qP+XGKLadl+pUGSEG/g6zzJx/+92ztY3SeM9OB9aaIh94eINPZP3H/PYw2Ia7O11EG0Vox/4828jf85JHpf7zcLwtIV4PzD/nQGsld0iwvcfSWREaO5/YwxODMTpjYQjKzLi4cUUw8Sz+nNRzkPnlqjHKHsvMlvs0XbZRetoKcaNo5YfhrN2yE707gbohGU9KeYUmQgw/xYRqLjIuJhd92Aetf21MGI0yP05w8J1/bUyYnfhTl6Fu5hiEI5nN07yt9aQwnuYY3QsWnZif7Ti1ewbiYwQvvf933KrFm7bYhGlXwkI1+fcoTGZRbv0ZIomzmVx8BoJkICKBCoqMkGPovPXAOOb5DayYiRkAft6gFa8W20TV9/ystbF9G8x3LX9nIH3a5aZPJfHsbB66H1K7Je28tgC9sSBGw/xrTyw+QXhmv1/Q9hrW6fZIOcY/9XDKNqHK3s7e+46sDd9Nvsuz0mABJQiUD2ReZj7lfJiXUtdjGU/b2Pwpcg7S+S1u371ulJFgsaSAAmQwOMRqJ7IPJ7tDIkESIAESKBkAhSZkgEzeBIgARJQmQBFRuXcp+0kQAIkUDIBikzJgBk8CZAACahMgCKjcu7TdhIgARIomQBFpmTADJ4ESIAEVCZAkVE592k7CZAACZRMgCJTMmAGTwIkQAIqE6DIqJz7tJ0ESIAESiZAkSkZMIMnARIgAZUJUGRUzn3aTgIkQAIlE6DIlAyYwZMACZCAygQoMirnPm0nARIggZIJUGQ2BBx8F2b164Ct68ynBjZiF9LhAAAgAElEQVQMr7TH1n1Yq7SIGTAJkAAJrBKotsjc2RiddWD8teVHx1Y5rL2y+NwLvob50vD/Rl80pMisRccHFCIgvjaa/OKn/xXPDxPM7xWCQFNTBKotMtGnZ4/HeNr+RPglSU0DRSZVnniiLAEPznvT//R38hPN8fFRF5OfysJR2nCKzE7ZT5HZCRtfqi0B93M3FJgmutfLL72mPgt+PMa6TwjWFpDChlFkdsp8isxO2PhSTQk4GL4Q85U62tcSGfkxgqkF9/vTdZ+0rSkihc2qmMgsK/e4G+4X3tUJef/+hS3P2ocFph+6aB01EITTQPO4i6vJHK78jczVZTo2Hi5zZ7AuOjCe60Gc+gGMkwHGN/KBvsjRIAp/Mb1C99VB2FpsoHkyhH2XSZY4zU78L6a4OjURzCHpOHjVw/hbkZUe/LiOm/j/7Z1Na9vK+/5fi96ElqaLf+iiWcU7QReGLgyBn6EQzIFiDhQTKKaLIArBBEr4QjCBAw4c0KLgRUGboiwOzqK4i+IuCl4EtChoEbj+jKTRkyX5IVbisa9CiayHmXs+92guzcw9Ui1kq7800D4dwM43Fc5ZwN+8FQa4cD530JDlfFFH+8zCZMGYfDbP2lETHTGWX2ZqTvG56xkI3JpBvXzVxzg3ew/2aXiPntqgzORC2tmd+ycy9zZ6R2GFFw29mMiPxEZD7cRaoku/msh4PwZo6WGeL+pBnrIR1nQYn5y5G0+KjH42xOjveiiGYRpSWPUWhtlx7oTIjG5NGDJfeY3/tw7zv5xb/c8EgxMpvJm8wus6X+afVKXI9L44MI1QRFP5adDfFg2VuLA/yPLpODBEYEUscNqLNqxsGXf2dlSzYOOLQ79+6gUPde63PpovwvpUKERqlp1WLyagmMhkCrTyxP8Ug4ao7DoaF+N0r2U2isSncTXfkKZzXkFk/tjo+g19HR0rna77XYqPju7XdKMvRUb22GrHfdi/w3MStuofMk+Gkcjo0EW+Rx0M78LugDvB4G0oAidWuvwQT5vhsRdtXN7OIuHzfju4jMSngcHPNA0pMoGtOhqfbMwiU3uo+4KjI+jppK+dXjWCBupNH+Nkr+VhhpEUn8ZgCeFPp8tfT0XAxehdICCy1x3l/DCF9d7IBAN0wRGziNBebOyVyESTk3MNbOjruz4ORYOomygYaAtPXF5kxhfBU/rhef5Agmu1g15KJkIuKTL1D3ZGEABIW7UORsnGORIZITAmnOQxYX10XaaM3y9DMWjO9478Uk8xPA4ak+wTaywyeWPyLqyTsBH6Jy2yuB+h4wtwG1be0B/isf48gQqdwT8bIpCsc/LhpuhvLCjxvZD0kXiAasvei26gd9VH03/YaGL4e0MGMxklCOyRyMRPXNleQ+wpBz15I5QO0cQ3VnyzxanEW7KRNOae/qNzfg3Dm6+XErbohi+MyJG26jD/i1JLzMkUiEUkQumbXQ55aCVj5t7XbiCImSEPKTKHH+eH/YRl8riWGU4Rou83YiV5Oh8LBCpRZG5uhkBU5/x7IOC+ssiI+c5PcShz7fgy7KE6MOW9RZHZjMMUSWWPRGYMM5yfqB0FCyr9+ZhwcWWwHc8FJJ/K5n25pMjMLLT8G0vONeTka8jJ/HSjH93wmYY5tiW2IWVrJCKZnoq8MDqezC8W4FLRjK5N956kiBRdK49nRWb8SQ7PhfNUKV8ErOryabiQgywY/z4Pgbgedv43RFfOyekGujeTaMgV7ggdiszzuOiZc90jkZFPUuVPaPLJLdVwzzkpvrGKGlb/kqhRXibPZKMPrCIynS+JMbEoz1VEZtXypG2VIlLEQh7Piky0f4kn5+y1cy7hjmciMIP1Nl2/9TfmfCRiVC/TPfZnMprZPiGBvRSZcgFZhv7jGuWlcrhpBkNJhU/wUwybwc2dKk90M68mMrKhKBIK3+ZoaC89eSvFouhaeTwrFEX7l+HDc7aHQNQj1WpoX0/m5w+Fqd96QX1+zSCO7fHc01iyGyKzVMVdUhiW4r5sWrL3lB9ZVZbVwp6MZ6ObN/ywlsgAUUNRMj8SzaFkeEuxWFVkojJmgh7KuPBYdQQifyzRs0z6OpqrKwmYcc6CodFs0Eh1pWHK20JAbZH5OYDh3xBF0UlpzNMrI3iaElFXCxYHpq/M/lpWZOJFaMXrRLJpB7+jG76gJxMdz4b3rikynt0LQ00LAgYgw781NK7TUWLrigwi/9Vh3qZDuPOpcG+VBKI6taLIwLPR8+c786ILAUQ94EP076osAdPeRgJqiwycaDJffzvA+H5BQxWFzGrQjS4Gt1N4D9ItHtxfY1jXXTTPywOYgWVFJggZDtaJaBBrXUY/3Hgy9MHD7IeN4Xkb3X/Ty+mjG/5vC25kY2DrbNQLF1nmLKpcU2SQEBG5tkbS9H7b6B+HizRzBHptkYEIOAgn/8VE8bWTeluv504xtgboHvdTkXfSY/y7PQTkeidNK353mV7SS96ektCSTRNQXGSA6U0rs9grMQmZ0wvwClfBx9fpn7JrWuSwV3yODBBI/01PiEtnTf9tR69oSZ8fp9cqEhn/qTKOTouircTNnLP6fu61MtII+TcSoRxbf43QkW9DyHuaLVh9v77IAPhT/JaAiJVuFryuRBaKf5+fwBRWtGA3rtfSh7pYbPuo0YPnLyEtWI+A8iIjiu3+N0x9w0JW7OxEc4RIvEfsvINmFD6sQbyfq/nuEtZdukcRXPM4kfHTmNnBt2+Sr7A5MtA+G8L+mYgOC42MejIvaimB8t8jdjaEk2emuDYSkVUm/sNMxR+xzuG6i3aCTfAeMRuzTI9KXvUokfETcTGx+ugcG+E71sSC2AMY4n1y1rgwX5k//24LARfTUfIde+LhqA3TKggG2BazaUelBHZCZCol9EyJRyKT0xt7JpOYLQmQAAmsTIAiszKyp7mAIvM0nJkLCZBAtQQoMtXyXTt1isza6HghCZDAFhGgyGyRM5KmUGSSNLhNAiSgKgGKzJZ6jiKzpY6hWSRAAisRoMishIsnkwAJkAAJrEKAIrMKLZ5LAiRAAiSwEgGKzEq4eDIJkAAJkMAqBCgyq9DiuSRAAiRAAisRoMishIsnkwAJkAAJrEKAIrMKLZ5LAiRAAiSwEgGKzEq4eDIJkAAJkMAqBCgyq9DiuSRAAiRAAisRoMishIsnkwAJkAAJrEKAIrMKLZ5LAiRAAiSwEgGKzEq4eDIJkAAJkMAqBCgyS9KK3iWW+WJk86bo62Ey4aIPnhV8VExe9oi/69v6iEx5KQmQAAnkEKDI5EDJ2zX70oXx2oj+H+jBJ2YXi8wYl4nrjOjLmBWKzNq25pWc+0hgRQL3YwzfG+Fn0aur5ytaxdOfiQBFZi3wMwyPlxWZTAa3JoLPQz/VzfcIWzOm8ycJlBIQn+4+b6Y+F65pT1XPSy3jwWckQJFZC/4jGm6KzFrEedE2E3AxHfXRfBE8eOlGD4Pz5hM/TG0zn/22jSKzlv8pMmth40W7ScCz0fOHj3U0PjlwAcTzguzJ7KbTly+V+iIzczA8a8N4qYdPTjXUjzu4HE39yp6LQnTrP3fQjOZHlrgmlVD1IhPdpGdOKmf5Izp+PER56MFqtro/bAzPO2gaB+GYugb9pYHmu0vYRRn9HqIpAiJ0E2NhYMi3EfpEf9lA92ZS7A9ZKP5VlIAH+6yNwXchL8G/qH5yuEwi2du/CouMh8l1OzP+G3TXgzkPDeZtjl/vbfSOwvP0g2AiPxIbDbUTC9Ocy9K7Vmu4U9cuOVwW3aRPKTKRbWmOkqem1WHeeqni+D+kyIgG5dcIHck3E4lXv/AlaP567tk5AlH9pcjsnG9XLZCyIuN+6YRP2jqM90OM7+PGz5tNMDpvof9fFscUg4ZoQHU0LsbpJ+vZKBKfxtUimdlVkemj8e4S1u0Esz8xO+9+jMHbsKd4dIlJfCjYikSmhpoYl9cNdG/GcB/EYReTq1boqy7s2E3ZVPh7hwhQZHbImY8sipoiE40Ba6ifOVi23YqE6cRKC4yEeNfHYTjskz9IJU/cUZGRxcv7e2+h7fdMmhj+zpwQiYwQmBYGP7IecdDzr9Vhzgl/Ji3+fDYCsTAU9WTj/YtC9+O0OCfzbA7dkoyVFBnvazeYf9F7KzwZuxi9C26S7tdsIyi9IRvDJoa/5L68v3soMpCLSstE5hC9b3lsY165Q5h5iLnvyQnEwhCLSTxUmt5HkXly9yiboZIiM744DETm1F66FwOMYYYLKGtH8aLK5AJL43U9muMpbwzjRnPRzTZXM6J5j/InvOiGf8o5Gd9YF1N7iMuPHTSTi0gjNmUik3NsDgB37AOBqP5yTmYf3F1aRiVFxjkLn6oKGuD8Essn8fQTWdGT2l6KTMmkfcwpR0ii4bKcY/nO4N4dJ0CR2XEHr1A8tUXmY/nMSZpDLDLlApK+Kv/XLvZkZFCEBv2NCftXdthL8ssREopMfjXZ470UmT12fqboSorM7N9WMFz2qh+sy8gUKv/nI4RhLsFHpLXqcFnBkODkf0bAYFPrZH4OYPiT821Y93MFBpaak8kRoLykuG8rCcTCsLi3v2iYOE6rfFh4K0HQqI0SUFJk8HOARhit1LpZFG4c85pehQ3zkQknEaIbn7HsVvUiEwU3vB7Mrdtxv5mo++XXoG1KZCLxyw8znlqdMM8cIWFPZtmKs9XnxcJAkdlqRylmnJoiAw/2abzCv3luY+rGwzuF62TuR+iEk/+60cXgdgrPX8shvObB/TWGdd1F83zRMFz1IoOo4dbRugpXyz+4GN/Ixj5sCDYlMqn85BoXwP0xQv+4FvSafGGjyCh2jz+JuZ7rwk38n1zJd5f1MErsdx/1cPckRWEmGyagqMgA+DPB4CTZ+M0/feXNvXi3JoxQaOLJ7PS1+qfsynQ5H5E+b/76+QZ46afDuSCGpJBm8j3qYHRjBgsc50RmXVs9OGf1hJik86yd9NB9LfbNlzEWxJxjG66wTG4bCcQPXfP3RLoeaXP1fBvLQ5s2SUBdkfEpeJjZA3RPDMjvu2jiVTEnXQzsWXF4szuBVfB+Lusu7wVd6zbcyRcFZm42Odwl/+befC6c8/i9bOIdYu1zGzPR+5I9j42JjADqYnLTTb/TLWQJyIYkR0ikLXkCtMnayrS2lICsGwvquKjrufV8S4tFszZCQHGR2QgDJkICJEACJFARAYpMRWCZLAmQAAmQAECRYS0gARIgARKojABFpjK0TJgESIAESIAiwzpAAiRAAiRQGQGKTGVomTAJkAAJkABFhnWABEiABEigMgIUmcrQMmESIAESIAGKDOsACZAACZBAZQQoMpWhZcIkQAIkQAIUGdYBEiABEiCByghQZCpDy4RJgARIgAQoMqwDJEACJEAClRGgyFSGlgmTAAmQAAlQZFgHSIAESIAEKiNAkakMLRMmARIgARKgyLAOkAAJkAAJVEaAIlMZWiZMAiRAAiRAkWEdIAESIAESqIwARaYytEyYBEiABEiAIsM6QAIkQAIkUBkBikxlaJkwCZAACZAARYZ1gARIgARIoDICFJnK0DJhEiABEiABigzrAAmQAAmQQGUEKDKVoWXCJEACJEACFBnWARIgARIggcoIUGQqQ8uESYAESIAEKDKsAyRAAiRAApURoMhUhpYJkwAJkAAJUGRYB0iABEiABCojQJGpDC0TJgESIAESoMiwDpAACZAACVRGgCJTGVomTAIkQAIkQJFhHSABEiABEqiMAEWmMrRMmARIgARIgCLDOkACJEACJFAZAYpMZWiZMAmQAAmQAEWGdYAESIAESKAyAhSZytAyYRIgARIgAYoM6wAJkAAJkEBlBCgylaFlwiRAAiRAAhQZ1gESIAESIIHKCFBkKkPLhEmABEiABCgyrAMkQAIkQAKVEaDIVIaWCZMACZAACVBkWAdIgARIgAQqI0CRqQwtEyYBEiABEqDIsA6QAAmQAAlURoAiUxlaJkwCJEACJECRYR0gARIgARKojABFpjK0TJgESIAESIAiwzpAAiRAAiRQGQGKTGVomTAJkAAJkABFhnWABEiABEigMgIUmcrQMmESIAESIAGKDOsACZAACZBAZQQoMpWhZcIkQAIkQAIUGdYBEiABEiCByghQZCpDy4RJgARIgAQoMqwDJEACJEAClRGgyFSGlgmTAAmQAAlQZFgHSIAESIAEKiNAkakMLRMmARIgARKgyLAOkAAJkAAJVEaAIlMZWiZMAiRAAiRAkWEdIAESIAESqIwARaYytEyYBEiABEiAIsM6QAIkQAIkUBkBikxlaJkwCZAACZAARYZ1gARIgARIoDICFJnK0DJhEiABEiABigzrAAmQAAmQQGUEKDKVoWXCJEACJEACFBnWARIgARIggcoIUGQqQ8uESYAESIAEKDKsAyRAAiRAApURoMhUhpYJkwAJkAAJUGRYB0iABEiABCojQJGpDC0TJgESIAESoMiwDpAACZAACVRGYKdFxh110TodYPTDrQxgkPAU49tZbh4zy4RpjeE+5B7e/M6Zhe5fl+uV+d5C9+8hJlXj2nypmSIJkMCWEthpkcGtCU1rY5jf/i/nEm8C66KP/nnJ/3cNaJoO42I8l+bspglNq6MzeowRiWQfphi+N+H8SexLbTowNQ31MwerasX0OihH49TC5KlEMWU7f5AACewagT0QGRNOgdemXzponjnwCo5Hu/+4cMtO8sWsg1FOwx+ITLENfh73DgaLhCwUue4bHZqmQTsqEppAZMzbyPrlNv7Y6OqBOJUVFZjCFj2z5VLlWSRAAntOQGGRceFclfQuRKPs9zAa6OT1Qt43oIvGWtPRupk+rhr4IpMvJEuJjMg9K2S/h2hqGg7P53tH5cauIzIexp/q0DQD7bNypr0TcZ6G2skQ03I1KjeTR0mABPaCgMIiA+DBg5vTe4g8V9L4R+dsYqMkn6VFJmOH+6UDTTtE/y5zIPVzAuvzCJP75M7VRcb7z0Rdb2H4K5lO3vYUg4YGTW9h8J19mTxCC/eJXutpG8ZfFjY0gLowS55AAs9JQG2RWUSupPFfdOlKx0vyWU9kPNinGrTXA5T3sQJB0d8OE+etKDJ/HJhHNbStxU3e9B8xv7SBnt9KcHfsZL+uaNCOhxSZHXMti5NPQF2R+W3B+i+/UNHeksY/OgeAN5stmGOYYfx1Ujx34+fThZ0zfLSWyHg2upqGxnVGYv6MYd8lM8kTlLx9ydImt6cYvq1BP77EeEHHxLs1Udc06O9GC1gl0+f2HAGKzBwS7thtAsqKjBhOarwrnz8onZOJ5mm6aIgJ779Hid5A1ulj9F9pqB1386PM/LmfJoa/s9cB64iMa7WhaQdonqbLF0z619H5IsUnT1Dy9s3bBXhwzgy0riZwfw3RemGgezPJFxC/t1MWbJCXPvflEqDI5GLhzt0loKjIuLBONLT+LR7iEU/ejSWe0HHXR1030L12MCsK2w17Fp0vBY/7t3003l3CyTm8usgE8x76B3uu5+R81KA1+olexwzDYw3pSLJlRMaD86mFriXFCvC+dv1ACBH6nOwrQQrMUnM2T3ujOGcicEOW38XEMtE+qgXRd/oBGqdDTMrm7O7HsM7aMF6GEXtaDfXjDvpWgdiGwRialh/kgeh48oEj8JEfEegHmgQ2F/4+K4qFBOBOMfrcQVOWUdNxYLRh3pTU3QcXY8HFOAgDXTTUjpronFs566FCW/2hPBf2WQM10Xt92Yblz9fl7cvxuTtJc9UPYJyYGBasJctJgbt2iICSIiOHbopExvsxQEvXYbwfwEnq0JyIzDA8aS+e8P45gKE1F5+XUzFWFpm7Pg5FXnO9oqA3ZVzFwgCsIzKioejmTNy7GL0TjW0HIymWfyYYvNWh6Q30U8N0OQV9hl1SZFpXI/RlaHe2IS8I9Xa/9mDoxQ2+/qaPcVagIhF5epFZZG/zJlnRQ2fc2+gZUkBzyjrn11hkHH/+LXHN6QjjK7GOKrEvZ14puPfCc17UYbw2EiKuw/iUeYh5hnrDLJ+WgIIiM0b/pYZao5+7IHE26sEwOhjORT8F8w+Ni8Qaj7tR+IRWDt2P9HrVx6rBxCLV1UQmuMnrjQ4us426Lz7ZaLPVRcb7PS3usYk8ji4xEYZHAtPC4Eeqb1MO6wmPSpEJGj7xUDHEOIy0c7+LB42gsZub2/o5QCMMXzc+WnF03oPoDcXio59mepNriUwGyDrDZaK3HTbuteM+7F+xPzx3Cue6i+5c4EYYCSh6IkYPVuKtF+4PKxYfvQs7EtNQZDQduq6j9c8U+DNCR+T9qo56dp+WmYcM11r5i48TvWRBIPaHju7X2P4MHf7cQQIKikyBF+7HGL5voHVu5zSiU4z+rkPTD9ASwwSpkN+C9KLdwdCclm1wouPhxo9xYhgrPriKyPhDVkd9jB9Er6UO8za+Gcfnh9DmhG51kYkty9/yRJauA1M8AR91lhLh/JSmsM+aqGk1NE7L5rvyr15mbywyuj+3FNMKrg7mtkQDmXxAcDH6O3i6P/yY/1Ttfevh0G/UMz3KZxGZhFikogjLCbmjTjA89qqX+zAmhkF7rwIRjntBUmTEsKyMbCzbl+YzvgjWUBWt7Yr8kdMDKi8Nj6pMYCdExjmvB/MJJ2ZmYr6HznHQXa8tMz+T40lxY4hFmwdFk/5+AEEP7SMN2os2hj/TiSwtMuKmP4rXqkyvDGh6ByNfEB2Yuob0UJnIZ/Mig18WOkca/OEiOWyWLtJyv/4zozkAEfZsLooEXC7V1FlSZIrEAr+CBa2a1kL0oO+GT+aagUHGV3HiUwxeBw1wah7uOUTGH6oVtjRK7I0tD7bE0Gdg/3ydic/165gQ0yhiUAqKjl4UKlm2LykywXCuWNBbyDXyR6/wLRyxddzaFQI7ITL4OUCz0UH/ZgTnxwyu68LzXExHfTSPmujbwXi1d2fBup2lJ7YXetKDc95d8EQ/DkTgsz/QlEpxOZEJJuKTPRf4jXTQOAdPgMkbWmYR3NirT/zL6+VfF+OvDsZiqFHMZX2086PM5OnwMLktCekW5z2hyMRP4pGB4UYQBKEl57j8YUfRABfMq8grw6CCw+T76J5BZIJFucusmUqWXTb4MigieSyxLYfuop6eFJRkXVty38xCy+/9iWAEI5iLEfMxyf9R8EEy/YQ93NxJArshMhnXuHdDdBuN3IgxfwL1ZRNmUQRRJq2lfoY3WO/b/NnLiIx3e4nLxNCYn4pI88jE+M8Y/SMNh9moL/+koBFN57tMdFnGztkI3XDoRDtqw4zCu9Mh1NFLQsNX8tRPy8QojETyhyhXf1lnxsLcn7Ins1hkEnNZsmFdUmS0ZLTXM4hMUH9WXbwpxXVJkYlYLCkoYQ86Jd4Rm6AHlQoQ8MUnuZ8ik1uhd3TnTomM+3OE/nEdzbO88MzYg95d318bIyZE7ZXmZ+I0UlvfekgNySQOLiMy8CdCEhclNv1V9tGwWeKAvxk0JulGdgWR8Wawz5uovTBgCJFJNqjZrJK//QZlvWi7ZDKP3V5GZHrZuZWoh7WgJyPCxbXMEGXUkBZcGx0vaUSlyC05LxGJTDP5VodF5IKetbA/3cvNXOfX22QvaRMiU1L2TPb8uR8E1BeZBw/T2yHMY7E+wkD3Hxu2PcLwc/gU/rGDpt9lb6J53IBxIhZUDmDd9IKInWg8en2H+2Pb0ZBDOp2lRCZ9SfxLLJLU0wEA8UGxtabI+Ost2mi86eDSFsOHYeOyqsjMhVmnrav610KRkfMZekIUomGdkrkDxMNNqUioSEQyUVWyoD8uYWRFTR6Tf6XILHxlUHhBJIptWEs/EM1gvc0RSWlD+Hd8cRiEJEdBLY8QmbAu+vNvq74BPGMXf+4WAeVFRi4iDLrnwWK63vklhiMb9t0Q4kk2/2nOg/PxEHmLHldzcXhjfsxfRLe2yPiLIMMw0kKDxhi8u4T9OxlXVdyTcX+MMPjYQ+9avFQzeU0FIuNNYb03oGs1ND+PV5wHKyxw6kC5yIg3GgSNaNrHcbRWUcBAVKf0XvpVQeGi3NzJbRGRJ4I/FomMFD5tSdHwbPTCUOy5hbIpGukfwbeBRGRdUXRZ8GkHIQrzk/zJ3siywhO+b0+ETK8QBZe2mr92kYDyIiMirKyzPqy7vAn94gbXd+afGWbRGoE13Rs+3aaikBJJrSUyYh7mTW3NhWsFZRZvrE7qSsJGGaW28nBZWU9GPrEvanRTdqz2Q4qMMSdiLibXbX+1unhjtJWxMxIRTUfjk42prANidfxNN1ykmfciUNngioZ0EK2YF3OAIiIvEBjxN9lIZ8sURAqKc0Ua45TYZ88Nfk+jRZDhWqBZ7MjCdTLRmhURKWim1tb4c5bhIs20IMjyJe1fdh/gvz3D97d4BVPf/zprZOmDh9kPG8PzNrolb+rIJ8C9KhPYAZGR+F2MLxow/rYwjVb2JxtcD7NvA5gfB7DupvCic+T1y/z15q4L1gYkVslnkllZZPw1KgdoXy+I3srkE/90Snpv8VnprbAh2eRwWRTFJRrdYj5pO1b7JUUm6sWGkUwHciX/3Ip2mb7n15Xge0JJcZDbxSvTY4GS58q/4p1yQz/KsFxkgOlNKxHeLa8P/+b6wIX9UfQKM+cmfqfn5YJyyrnHWPzS1+tG9sN3ywpK3nlBntN/Q3FP2JbNv+hNHdI7/LtbBHZDZNwJBic1aC/EB8qGsH/KBR5JkQkd9xBOdot3W7279J+2lnepDIsOX5cRhmTWk2GumcRWERmxKrr9povh0ivsPUz+6aFz2ovWB/X+Chqj/CHCjHHRz7DREGHgiyLLxPEPrYJX30QJindbY/y5iZp4L1z0Qs/k8cdvS5HRX9RSDbD/bq7PI0xlNSjIyv1uof+uifqLsPEN37Flzb0tIp2A+60fvwvMv6aPIEq+uPFNpwC4/w1hnhiIBFE2yrkiE1zt3mXsjd61NlxEki8AACAASURBVIZb9NAk3iN2nvO+s9zoyjz7l92XKOHMDr6ZE71jTbwvTXwQL3lvJs7n5k4TUFxkXExuumgctfy1MKJr7v6aYOa6/loZ8XbhdtGczMyGGb7vqnay4gekHqYYHIuGSQxflK9mX0pkhPBd9B4VVp0ashGhz9E4xTL1N2xIShq4VCr+EGHZxHnq7Mp+SJHJe4qvLFMmTAIksBIBRUUm6FG0/8p5s6s3g3NjoimfTrU6Lr8XMXFhfxCvwkiOQRedm97v/Z5kJs/Tx+WvmdVF9zrxvjR5IPo7gzMqeRKNzltiQ4Rm/18fztJRSDLNKYZ/dTG4W/DoL093x3CWPVdeU8FfikwFUJkkCWyYgHoi8zD1G+XE3Gc+EhH++7IF82vyrcV5p7qLV6/nXcZ9z06AIvPsLqABJLCQgHois7BIPGFfCFBk9sXTLKfKBCgyKntvz22nyOx5BWDxlSBAkVHCTTSSBEiABNQkQJFR02+0mgRIgASUIECRUcJNNJIESIAE1CRAkVHTb7SaBEiABJQgQJFRwk00kgRIgATUJECRUdNvtJoESIAElCBAkVHCTTSSBEiABNQkQJFR02+0mgRIgASUIECRUcJNNJIESIAE1CRAkVHTb7SaBEiABJQgQJFRwk2PM3J2Jz5FPXtcIryaBEiABNYgQJFZA5pKl0Tfetd08IuEKnmOtpLAbhCgyOyGHwtK4cE+TXxyd9mPkhWktnD3vRN8EfGvFT8CtzDhCk5QydYKil9VkuJro8kvfuovG+iIr5T+qSpHprvtBCgy2+6hR9rn3V36H3DTX7Zh/XpkYosuvzXhf8/9eIitH5xTydZF3LfiuIfxRSP1GWy/LsjPSh91MKq6/m0FBxqRJUCRyRLh7/UJqNRwq2Tr+h55sivdL51QYOro3MRfek19Fvx4iEWfEHwyg5nRkxGgyDwZ6j3ISKWGWyVbt77qjNF/JYZldbRucmTk5wANv0ejo2d7W18aGrhZAkqKjPxYlXkrYLhwPnfQeKkHQzUv6mifWZiUjQHfj2GdtWHIa7Qa6scd9K0Jcr9y/3uIprhJwmEg74cYd66jFt44B286uPyWe2XsLXeSzlM/gHFiYnibM7D0x4F5FMyl6G8L5jcSN252Qn920wxYyKGK8G/zJiev2MJoa3Y79MfV6y/i+Rz9pQHjuAPrZ3QagBmGx/E5qeGRTN7+sZI5oZl9ic6xZKqhdtQMxvJzsTow/fRNOMKceweX7xo40ANbakdtmNYE6eZsc7YmCXAbwK0Z9GJe9THOBZKYGzy1M37JvYA7d4iA0iLT++LANEJxyTRq+tv8rrn7tQcjbIzyGkX9TR/jrEBJkWkOYP/bDsUl27jWYd6mmzVZT7wfA7Rkni/qMF4bCYHTYXxy5m487z8Tdb9MeVFhUwwaQf6HH+evXV9kPDifjOJxdU1DIOyyZJtouF3YH+qhKOo4MAwYr2Ox0V7kzSVJkelh9M0s8Gf2qXoTtspy82+SwPji0PefXvAQ4X7r+/OC/v1WKETJFLm9SwSUFplAJHQ0PtmYhe37bNSLGud0gwgg8fRvfLQwuQ9d+eBiYsXio2eftqTISCE76mB4Fz5iuxMM3oZClzfh/cdG1xeYOjpWeijB/S7FR0f367xATf8JeyR6C8PEpOn4ImyUj0w4WUGcq51x47qwJ3PXx6Eoo96AaU/hPcSJea6L6Z0dM4sPxVtrDEFNrxpBAyXEPdlreZhhJMWnMciM5UuRCYXet3cWCHXyOj3s6cQWxltr2BpfzK2YgIvRu8APc/XrYQrrffahpQuOmMX09mFLcZHJPq0Kl7mwTsJK/0+yUXcx+jsQg7ynf3Gl960XNLJaE8PfCfcnRSavYZeNs9YLhm8Sl0pBODzPH0hwrXbwFJ8nUJhiGApY1DO764ciWkf/LpFR4ebyIhP1gP4ezfWsCpNPHli14b4foeMLcBuWFPxkeojH+tMPDAmRyQiwf/m9hbb/QNBMiXMq6VVtTV28mz8i/8uHqZK/saDE9SvpI/EA1ZbDrbqB3lU/GHLO3lu7iZKlShBQWmSKxELO2WjJ7rs7Qse/aQwMUvMKCRqYYvA6EKjOl8RjdSQyBY1W8nhSnKJGsiTPX+F8T45A+ZZFDbGO1j8W+v5cTZ64JsuR3I4bgbhhSB6Pt72v3UDw9Ab6t4nyx6eUb63YcIuIJL83mu05JnJxPuY9MEiROUTv23wPEJDHs8N7iYRXtDVx5c5ubkRkHmawP8WhzLXjy7CHKn2SeYDbWZosmCSgtMgUNZq5IhP1NkqGUADIaw8vEj2PSEQKro2OZ26gmYWWL2xyrkHMN2T+GwfhHEjmWumhVA8raHALgwES18Sby4sMEj0n0fjrL1voXlsY/85ryOMcoq0VG+7xpzhYY45LyCkKPkg+MEQiUsRMNmgUmcg3lW3E9avzvyG6co5UN9C9SQRfRA95RT6rzEAm/MwE9kdkZAOoFQhF6AgpMqleUCQiBddGxzM3ULQ/EIdgDqloO3NtqmLMMPw/eV0Lw+WCxMIU4kagSJRTWcloPTnUEQ6ZCMHp2wsyloxzh/7SuYhfEeuSYZmIGUVmHuBW7JnBeivrZvBXf2NirqpE98L8kPJWFINGVEZgf0TmvzDMcpHIhMMzxlViPie6QdYVmTIBWezb6U0rFfEVzc8svjQVZrycyMhEPbg/bAzP2oh6E0XrIOQl64pMSkBkYmV/ZU+liKs8zp5MGcVNHYt6pFoN7euCZQDfesHQ6OtsEMemrGA620pgf0QmGroqmR+J5lC0dLTXuiITDevomdDfFarDr2EY/qyj+88wnCivZk6m0KoHF/ZZGNG2TMTWkg1JNAewZM8ntk+KyAZEZklb47x3dyvyxxI9y+QDSzyXV/AQ5vdag6HRojDn3aXKku2PyIhJ/ZK1JaIqiJtFFzeY3kuHWa4tMvEitNV6H2HFTCzKrJ8F62EiG7XidTnpar3qcFn66uhXxKAFq2jU7OcAht9AFUWLRakFG9H5y5ZFXr8BkYnyXtJWmfUO/11XZODZ6PlRggUPP1Fwy+GSEZE7DHkPi7ZHIpMQES1YWxO9GfbBxfimGy7qy7lRoga24EktOp7zZB2FHGuoHfcx+uHG4cEPHmZiSOq8je6/2Zbbg/MxWOSmpcKmPThRr6KDUW7ob7ImLy8yU3uI0d0Urpue6PfuJ7AK16wk83Jg+o2NBv3tAOP7dDrJM4NtscYinPwXE8XXTuptvZ47xdgaoHvcz4SGb0BkRC9zJVvnreeemIBc76Rpxe8um1t/Fl/OrR0msFciAyx4U6yWv/oekYisITIApoVvCYgnTLOvhonnYeow/8s01okeznwPSTbAcdrR5HlqGGReEBdOxOstDH5mbMncHLHdOfnnzb2IssiIpJR9iet1M/O6ElnG+TIE5sjjJXMywi+Zua4UpzxbM2XlzySBKayTWjDvkuPH3DdpJC/n9s4S2DORCfwovnnRf9eMJ7TD94hZ3wvWhjxSZPxcZ3bwrZWj+EasHRlonw1h/8zkGw0vaKgnQ6mT1TDRQ5JDacHhuIFNNZpzN/58Az390kf3xICRsFG89PDAaKN7PcI0Y2bSnOS2+1/w7jP5LrHIjsKGW7xxoY/OsRG9f0wTPjnu4NIaY5Z480C6jPNlSB8vFxlx7uq2JkvK7TQBF9PRJTpvZFh+UHfEe+SWrDrp5PhrJwgoKTI7QZ6FIAESIIE9IECR2QMns4gkQAIk8FwEKDLPRZ75kgAJkMAeEKDI7IGTWUQSIAESeC4CFJnnIs98SYAESGAPCFBk9sDJLCIJkAAJPBcBisxzkWe+JEACJLAHBCgye+BkFpEESIAEnosARea5yDNfEiABEtgDAhSZPXAyi0gCJEACz0WAIvNc5JkvCZAACewBAYrMHjiZRSQBEiCB5yJAkXku8syXBEiABPaAAEVmD5zMIpIACZDAcxGgyDwXeeZLAiRAAntAgCKzppNndzbsu+zXLNdMjJeRAAmQwI4S2BmRcX+OcJn8EJmmQXwUrHk12bjrpteN8AuAOrJftJzPrOgjYgVf2ZxPgHtIgARIQFkCOyEypZ83Lvwa47o+82CfJj4NvDD9MS5fGzDk/+irkxSZdT3A67acwP0Yw/cGdP9rrKznW+6tys1TX2TcETp60OjXP4ww/RMz81wX09nmP/zq3V2i+UKD/rIN61ec31Jbt2bYC+LNtxQvnqQOgYcZ7PMmaqlPfbOeq+PAaixVXmS8r92g0X7Vx7gaRptNlSKzWZ5MbQsIuJiO+v6Dl6Zp0I0eBudNPkxtgWe2wQTlRWZ2E1bmj8428FxsA0VmMSOeoRYBz0bPH03Q0fjkQIwdRPelxp6MWs7cvLW7IzIL50ZCeN4MY2uA7omB+gs5t1JD/XUbpjXxb5A8zPFNI68J/jZvVowwW1JkovwKyhUdPx4ia4FzFtgmgxLc7xbMk3o4jFFD/aQPO3tRotDB+QYOwmFI/aWB9tkQTsk1icu5uXcEPNhnbQy+x0PTUf2kyOxdbcgWeM9EZobhcVokRPc++V9/O8Q0Syn1ZJY+f5tFpnkzwfiiEU7Apu3W9A5G99mCephctaLzRXSeCFiQYqPpBsxbL3sRf5PAHAGKzBySvd2hnMjIp/SkMJRtm7dJ385g/dWCeTPC+JeLqLl88DAd9VD3BUdHZxQ/kSWvjrdjsdpmkdFf1HzBqB33Yf8OSzsboXcUCI5xlZZTMb/lRwQddTIBDW4sPnoXdiK4ImbCLRKICVBkYhb7vrVnIlPu7vH5YdCrKRiiiq9WQ2SE+NY/2HNDgNN/wnmst1ZiqG2Mvi8+h+jfxSWNt1xYJ4E4rSyscSLc2mICsTBker2Z3r6oV4vqQJwW52S22OVPYppyIpOlElXmhcKQvXL+9/JpKSIyx/lDf5DzQsn5nLs+DkVj8nqQO1woaEXipEqQxbyLuaeEQFT/c0QlO1pAkSkByUMpAvspMrMxrOu+P/kfLZIUiyVf6rvVk1lBeGf/toKy6wfxwlG5gFT+lXyS4pSqTvxBAgGBWLDYk9n3OrFnIuMVT4Qnn94WNs6K9GQWliOu/nGjsHioRKPIxOC4lUsgrk8UmVxAe7Rzr0TGs3th5FQdnZsx3GjmP/B4dGMsbJx3WGQoIHt0+1dX1OheYghzdZAVSXmPRCZ+59jhef67AaIbY5tE5tSOo+ASlWryPyMY3soRhSgCb2E5EgnKeRqdT54JKnu1GdX/ZK++YJtzMntVNR5V2D0Smbj3kQ3d9Qm6Y/TfbM+cTPS6nJyJePebGYZba8gbulpLZDwbXb9B0dG6SYc2P6qG8WJlCFBklHGVUobukcgAzlkoIkc9jOS6EW8G57oLI1zd7kfRLOwBxIK16IlurjbIHsOiYYTfQzRlo38VvongwcX4phMLjDi+qZ4MgPFFPegdaTU0z0eY3CfGE//MMLGH6P/VhfV7rlTcsecExMto3cT/yZV8d1kPo8R+l2us9q6m7JXI4NcQraSYJIcCdAO9D+2C6LKib8JkJ8mbGGYa4KWfDueETQzvhaKYtFNsH3UwujGD+aUNigwwhXVSC4UmWzb5uwWLr5fZu4aivMDxQ1c21Hnu91w9L0+ZR9UnsF8iI/w1s9E/iV+Vor9soHNuYSIW+ctextyN8BwiI4x14Zy3o9Bq/x1i5zZmDwBkT2ejIhNU6Jld8G63GxvTRS9DUP+eYAlWJkCRWRnZHl2gvMjska9YVBIgARJQjgBFRjmX0WASIAESUIcARUYdX9FSEiABElCOAEVGOZfRYBIgARJQhwBFRh1f0VISIAESUI4ARUY5l9FgEiABElCHAEVGHV/RUhIgARJQjgBFRjmX0WASIAESUIcARUYdX9FSEiABElCOAEVGOZfRYBIgARJQhwBFRh1f0VISIAESUI4ARUY5l9FgEiABElCHAEVGHV/RUhIgARJQjgBFRjmX0WASIAESUIcARUYdX9FSEiABElCOAEVGOZfRYBIgARJQhwBFRh1f0VISIAESUI4ARUY5l9FgEthSAg8z2NddtI/kJ7x1HLzp4NLm97q31GNPYhZF5kkwMxMS2HECvyx0jjRoWv7/+pkDb8cRsHj5BCgy+Vy4lwRIYGkCE1wagbjU/x5ifB/KiefCuWhA94VHR8+mzCyNdIdOpMjskDNZFBJ4NgK/huhdjHN6Ky6sk7B3824E99kMZMbPRUBtkZk5GJ61YURjwBo0/QDG6yY6/07nmM5umkF3/syZOyZ2RMePhygeRXYxHV2ic1xHLRwa0F8aaJ8N4RRfFOQn7X2ph8MKNdSPO7gcTYtvPjHO/bmDZlTGJa7xc5N2GjjQ4yGM2pEB46QPp+Run90OYZ4YqL+IrxNlNI47sH7mouNOEigkMP0nvO9K76vCy3lAcQLKiox3a8JINJ5zY8E5QhKJSM4x4cfoeNHNcG+jZ0iBiBvgKO+i6+Bhct2ORCk6PzF+bd7m1CSRnxzn9sXTSAlq7cTCvJSKdKawTuTka46dWhPD3zn5wYPzyQiHN/Ku05BrZ15S3EcCIYGF9xVJ7TQBRUVmjP4r0QjqaHyyMf2T8JHnwv01hv1j/lE9quxricwYfdngv2iib0/hPYT5ei6mtwN0T63cHpD7pRONSxvvE2PWALzZBKPzFvr/Jcrgb04xaIRlvBinezqzUSQ+jat5mXGtdtBTOupgeOemhjA8d4bJ7RizvOHxuz4OhfDpDZjJ8gk7XRfTOxuT+6yd/E0C5QScs+DBTC+478qv5lHVCagpMr+HaPq9gA5GSYFZ4I3HiMz0uhE03HoLw18LMkoe9mz0wh7XKhE2kTCdWGmBkWlHgmAiO/jnnAW9kPr/JvLspf5GfP4epYRpqYt5kvIEIv8neth5vW6xr3mzaGw4xHE/Qsev/4fo3ymPiAVYg4CaIuPZ6Po3go7GhQNX9igWAIhuooInquj43LDXFIPXQcPduJ7vOZRl633thuLUw/LBNS5G74L8ul/zuhwiRwc9n0FzTvSmV0bUk7F+Fl0/b3VsawP92/me4PwV3LNLBKL6vzGRmWL4NuzFnNp8cNmlyrJCWdQUGTHrcNOK5w70A7ROB7DuZqUVObqJVhUZd4SOf+MZGKw48T2+OAwa/JVusjHMsPfjT9S/NmDM/Y8DD+bmSf44MOXQnqah1uigf7PMUFfcKIinVf1lC91rC+PfywvVCnWPp+40AQ/OWT182DHhrDDisNNY9rBwyoqM8JX77RKdRmaCWwjOuY1ZTu9mbZGJhueKJsyLa44cutIKhC3/SgfmEk+TcihjTmREon8msM5aqcgycX6t0cXwe1kvxYXzuYNGIrJMCk6fK7fz3cW9GQJJgenB5jxehs9+/VRaZKSrvPsJ7Bsz8ToLDfrb4Vzk1UZEZpX5GDGoFc6PaB+zMyfS+ry/scjkCkjeJUX7HjxM7yxcvmskBKcO83ZR78SD+8P2Q8TjUGYdrZvVhguLzOL+XSXgJnowHYxWvF92lco+l2snRCbpQNc2Ufd7AfpcuG0kMgVDV5P/hXMZc3My8fBV2yrrBSQtCbZn/7aCIYNXfYznDxfsmWF4HMzJLD3BWpBSareXGA6bK2PqzPSPBxe2HPrQ5wMN0ifzl6oEovtjiV50fr1MCgx7MKrWg03bvXMiA8QNdOvfdARMNLH9ejDXy3G/SXHSoM01wB7sD+H6mKMVx5d/DtAIRW+VXkA8eb9ifotqyK0ZiJ5uriB6AKIhwxasNNZFOfK4IgQeJzIUGEXc/ORmqikyP20MR2NMXTdeqyLQeS4mVi/syTTmJ+mjhlJH62oShAY/uBjfdMJrgt7DvMgAiMRCg250MRRBBnLep3SdjAf7VC7grKF5bmPqxkNVhetkotDPIL/BbWJdDjx/LZB13UXzPDsM58L5YsH5MYObyMfH88vBpYz2+TAf7TO1hxjdTeevu5/A+hBO4jbmBfrJay0z3DICCYH5f11YP124btH/uO5vWSFoTkUE1BQZ+TRe2K3X0bqe5kSaJRv8UFBkGkcdjG7MIGJtricT0He/9srfMlBwnZiEH5SuwM9fSb/wrQYiAuxTdhAu7snJwIC5v0f5QxnR/JFkkv2rtzBYISS6ojrLZLeNQPTwlrmnsvVH/C66R7atTLRnYwTUFJmfI/RP2zBex2G8QQSUgfbpAKOfZfMmLpzzNozw/WH+e8dkNJq8WcpuhPsxrPPku8Q01I6a6JxbGJdG0XiY2QN0TxLvEhOvijnpYmCXhF67kyA/4yAK2RY2N99d+iHb8zXBhXPdQ+fYiMoYiEzwzrP+jZMbeSfSmX7p+/al3gWn6Tgw2uhejzAtwzpvCPfsCwF53+SJSnZf2b21L7z2rJxqisyeOYnFJQESIAFVCVBkVPUc7SYBEiABBQhQZBRwEk0kARIgAVUJUGRU9RztJgESIAEFCFBkFHASTSQBEiABVQlQZFT1HO0mARIgAQUIUGQUcBJNJAESIAFVCVBkVPUc7SYBEiABBQhQZBRwEk0kARIgAVUJUGRU9RztJgESIAEFCFBkFHASTSQBEiABVQlQZFT1HO0mARIgAQUIUGQUcBJNJAESIAFVCVBkVPUc7SYBEiABBQhQZBRwEk0kARIgAVUJUGRU9RztJgESIAEFCFBkFHASTSQBEiABVQlQZFT1HO0mARIgAQUIUGQUcBJNJAESIAFVCVBkVPUc7SYBEiABBQhQZBRwEk0kARIgAVUJUGRU9RztJgESIAEFCFBkFHASTSQBEiABVQlQZFT1HO0mARIgAQUIUGQUcBJNJAESIAFVCVBkVPUc7SYBEiABBQhQZBRwEk0kARIgAVUJUGRU9RztJgESIAEFCFBkFHASTSQBEiABVQlQZFT1HO0mARIgAQUIUGQUcBJNJAESIAFVCVBkVPUc7SYBEiABBQhQZBRwEk0kARIgAVUJUGRU9RztJgESIAEFCFBkFHASTSQBEiABVQlQZFT1HO0mARIgAQUIUGQUcBJNJAESIAFVCVBkVPUc7SYBEiABBQhQZBRwEk0kARIgAVUJUGRU9RztJgESIAEFCFBkFHASTSQBEiABVQlQZFT1HO0mARIgAQUIUGQUcBJNJAESIAFVCVBkVPUc7SYBEiABBQhQZBRwEk0kARIgAVUJUGRU9RztJgESIAEFCFBkFHASTSQBEiABVQlQZFT1HO0mARIgAQUIUGQUcBJNJAESIAFVCVBkVPUc7SYBEiABBQhQZBRwEk0kARIgAVUJUGRU9RztJgESIAEFCFBkFHASTSQBEiABVQlQZFT1HO0mARIgAQUIUGQUcBJNJAESIAFVCVBkVPUc7SYBEiABBQhQZBRwEk0kARIgAVUJUGRU9RztJgESIAEFCFBkFHASTSQBEiABVQlQZFT1HO0mARIgAQUIUGQUcBJNJAESIAFVCVBkVPUc7SYBEiABBQhQZBRwEk0kARIgAVUJUGRU9RztJgESIAEFCFBkFHASTSQBEiABVQlQZFT1HO0mARIgAQUIUGQUcBJNJAESIAFVCVBkVPUc7SYBEiABBQhQZBRwEk0kARIgAVUJUGRU9RztJgESIAEFCFBkFHASTSQBEiABVQlQZFT1HO0mARIgAQUIUGQUcBJNJAESIAFVCVBkVPUc7SYBEiABBQhQZBRwEk0kARIgAVUJUGRU9RztJgESIAEFCFBkFHASTSQBEiABVQlQZFT1HO0mARIgAQUIUGQUcBJNJAESIAFVCVBkVPUc7SYBEiABBQhQZBRwEk0kARIgAVUJ7LTIuKMuWqcDjH64FftnivHtLDePmWXCtMZwH3IPb37nzEL3r8v1ynxvofv3EJOqcW2+1EyRBEhgSwnstMjg1oSmtTHMb/+Xc4k3gXXRR/+85P+7BjRNh3ExnktzdtOEptXRGT3GiESyD1MM35tw/iT2pTYdmJqG+pmDVbVieh2Uo3FqYfJUopiynT9IgAR2jcAeiIwJp8Br0y8dNM8ceAXHo91/XLhlJ/li1sEop+EPRKbYBj+PeweDRUIWilz3jQ5N06AdFQlNIDLmbWT9cht/bHT1QJzKigpMYYue2XKp8iwSIIE9J6CwyLhwrkp6F6JR9nsYDXTyeiHvG9BFY63paN1MH1cNfJHJF5KlREbknhWy30M0NQ2H5/O9o3Jj1xEZD+NPdWiagfZZOdPeiThPQ+1kiGm5GpWbyaMkQAJ7QUBhkQHw4MHN6T1Enitp/KNzNrFRks/SIpOxw/3SgaYdon+XOZD6OYH1eYTJfXLn6iLj/Weirrcw/JVMJ297ikFDg6a3MPjOvkweIe4jARJIE1BbZNJlmf9V0vjPn/yIPSX5rCcyHuxTDdrrAcr7WIGg6G+HifNWFJk/DsyjGtrW4jmj6T9ifmkDPb9HoOalJEACahFQV2R+W7D+WwC7pPFPXunNZgvmGGYYf50Uz934+XRh5wwfrSUyno2upqFxnZGYP2PYd8lM8gQlb1+ytMntKYZva9CPLzFe0DHxbk3UNQ36u9ECVsn0uU0CJLDvBJQVGTGc1HhXPn9QOicTzdN00RAT3n+PEr2BbLUYo/9KQ+24mx9l5s/9NDH8nb0OWEdkXKsNTTtA8zRdvmDSv47OFyk+eYKSt2/eLsCDc2agdTWB+2uI1gsD3ZtJvoD4vZ2yYIO89LmPBEiABABFRcaFdaKh9W/xEI948m4s8YSOuz7quoHutYNZUdhu2LPofCl43L/to/HuEk7O4dVFJpj30D/Ycz0n56MGrdFP9DpmGB5rSEeSLSMyHpxPLXQtKVaA97XrB0KI0OdkXwlSYJaas3m6W2p8fhhE2TXKhhSnGLwWwR05vcKnM5U5kcBeE1BSZOTQTZHIeD8GaOk6jPcDOEkdmhORGYYn7cUT3j8HMLTm4vNyqtLKInPXx6HIa65XFPSmjKtYGIB1RMaFfdbNmbh3MXonwqM7GEmxMbP1JgAAEgVJREFU/DPB4K0OTW+gnxqmyynoU+/6OUDDjw4sCY7wWQqRacNKBUc8tbHMjwT2l4CCIjNG/6WGWqOfuyBxNurBMDoYzkU/BfMPjYvEGo+7EayFEVWAH+n1qo9Vg4lFtVpNZALRqDc6uMw26n6DmW1QVxcZ7/e0uMcm8ji6xEQYHglMC4Mfqb7NltwtYaRbSZj3+CLs7XAeaUt8RjP2kYCCIlPgpvsxhu8baJ3bOY3oFKO/69D0A7TOrUzIb0F60e5gaE47nR++ik4RGz/GiWGs+MgqIuMPWR31MX4QvZY6zNu4cfeHh+aEbnWRiS3L3/JElq4D09ChHXWWEuH8lKawz5qoaTU0Tsvmu/KvXmZvMHclQqrz1igFPT8RDdfLi8hYJgOeQwIk8GgCOyEyznk9mE84MTMT8z10jg0YL3XUlpmfycEpGjKxaPOgaNLfDyDooX2kQXvRxvBnOpGlReaPg95RvFZlemVA0zsY+cM8DkxdQ3qoTOSzeZHBLwudIw36m+TcT7pMS/36zwwXuwYLXs1FkYBLJZo5ybPR04P054REDpXNCXMmDf4kARKolMBOiAx+DtBsdNC/GcH5MYPruvA8F9NRH82jJvp2MDHj3Vmwbmfpie2FeD04590FT/TjQAQ++wNNqRSXE5lgIj7Zc4HfSOsQjXPwxF48T7P6xH/KRNF1wfirg7EYahRzWR/t/Ciz6DIPk9uSkG5x3lOIDDzYH8LX7GSGxGRgwOpvTIgKyQ0SIIENENgNkcmAcO+G6DYauRFj7tcejJdNmFZBuG4mraV+ziy0NA29b/NnLyMy3u0lLhNDY34qIs0jE+M/Y/SPNBxmo778k4JIsnS+y0SXZeycjdB9FURhaUdtmFF4dzqEOnpJaPhKnvppmRiJAIMGav4Q5eov68xYWPxT9lhSk/tBz0/TGhhkepbFCfEICZBAFQR2SmTcnyP0j+tonlmlr6v37vr+2hjd6MHeRNTRtx40rYW8RfPLiAz8iZB89/qr7KNhs+w5gaA0b5IhdCuIjDeDfd5E7YUBQ4jMWdGrRDP5+u9VWy/aLpPSBn7GAQCSg2f3gqG60vDmDWTNJEiABBYSUF9kHjxMb4cwj2v+Cx67/9iw7RGGn8On8I8dNF8bMF430TxuwDgRCyoHsG56/gp2LTPMspBYzgn+/EnB2P9SIpOTpr9LLJLU0wEA6VPXFBl3itHnNhpvOri0xfBhMLezssjMhVmnrXuqXwFjsYZIrJmJh9DalozFfipLmA8JkECWgPIiIxcR+q+/12qoH3fQO7/EcGTDvhuip2UXK0oEHpyPh8hb9CjPWO5v2EB/zO8FrC0y/iJIHa1/kutishaNMXh3Cft3HIUGFPdk3B8jDD720LsWL9VMXlOByHhTWO8N6FoNzc/jFefBsuVc8PveQttfM9PA4LsMBkis91lwOQ+TAAlUR0B5kRERVtZZH9Zd3oR+cYPrI/0zw6zsLc7LcA9fyV/0NoC1REbMw7ypwfiUWX2/jD1FIiPeWJ3UlVRaFYiM/z63cJ4nd3FpyoBH/oh7L42G+PCatoGHh0eaxMtJgAR8AjsgMtKTLsYXDRh/W5hGK/uTIuNh9m0A8+MA1t0UXnSOvH6Zv97cdeML8X2V4qfmlUXGX6NygPb1guitQnOdkt5b0UUViEw0IS+EpphPkUUr779NhkxnF62unBovIAES2BCB3RAZd4LBSQ3aC/GBsiHsn3IsPikyIbGHcLJbP/DfNzb6Ic9dhqgMi67DEPM8xkGwPifns8sytVVExv0+QPtNF8OlV9h7mPzTQ+e0F60P6v0lhqiKhgilVdm/ociIMPBFkWXi+IdWwatvkul6GH9uoibeCxe90DN5fNPbcvGlnJvZdPpMjwRIYB0CiouMi8lNF42jlr8Wxl+s/muCmev6a2XE24XFWH16HUmIaWbDDD9lXDuxkIzPWgjyYYrBcbAI0Hhfvpp9KZERwnfRe1RYtQjbFoso/bkpEfpcODSWV7p1ejLGdoUHew5MPwxbR9HQZV7JuY8ESKBaAoqKTNCjaP9lYnibkQdvBufGRPOFnA+o4/J7EUQX9gcx3JW30LHommC/93uSmTzPP39mddG9Trwvbe60GZzRGO5aw3eZxERo9v/14awclj3F8K8uBndL9urcMZxlz82YWM1P8dmC4LPQQYRZNbkwVRIggdUJqCcyD1O/UZ4telIX4b8vWzC/lkVnCWDu4tXrq3PlFU9F4H4C62MwRCg+C734E9JPZRjzIQESEATUExn6jQTCCLogbD3ssepG6oWihEQCJLAdBCgy2+EHWrESgSCgww9VfmmgveANDyslzZNJgAQ2SoAis1GcTIwESIAESCBJgCKTpMFtEiABEiCBjRKgyGwUJxMjARIgARJIEqDIJGlwmwRIgARIYKMEKDIbxcnESIAESIAEkgQoMkka3CYBEiABEtgoAYrMRnEyMRIgARIggSQBikySBrdJgARIgAQ2SoAis1GcTIwESIAESCBJgCKTpMFtEiABEiCBjRKgyGwUJxMjARIgARJIEqDIJGlwmwRIgARIYKMEKDIbxcnESGC/CbjfLZgnBg704O3Y+ssGOp9HmP7Zby77XHqKzD57n2UngY0R8DC+aPif/k59gkGTX2vtYPRrY5kxIYUIUGQUchZNJYFtJeB+6YQCU0fnJv7Sa+qz4MdDLPqE4LaWj3atT4Aisz47XkkCJOATGKP/SvRYdLRucmTk5wANv0ejo2cv+qQtke4aASVFxjkLuuDmrXCHC+dzB42XOvxu+ot68BGrsjHg+zGsszYMeY1WQ/24g741wZJfud+1esDykMD6BG7NoBfzqo9xbioe7NNw2OzUBmUmF9LO7lRaZHpfHJhGKC5y7Df8q7/N75q7X3swwknJvLFj/U0f4zKB2tmqwIKRwHoExheH/gOefubkJuB+66P5IhSZQiHKvZQ7d4CA0iITiISOxicbs/DxaDbqoR52zYOeTsJLiW678dHC5D489uBiYsXio/NpKwGNmyRQRsDF6F0gIM2bWfrEhyms90YmGKALjpilMe36L8VFJm8M2IV1Elb6f5Ljwy5Gfwe9nsOPTm6X3fvWw6EvUE0Mf++661k+EkgTmN00gyHnzKhAXo8/FpQZhsfB/ZZ8qHO/D9CWvRfdQO+qjybvrTTwPfmltMgUiYWcs9GS3Xd3hI5fyQ0MfhZ5d4rB6+CG6Xzh7EwRJe7fTQIbEZmHGexPcShz7fgSY/9WcmBSZHaz4iwoldIiEz9NpUuZKzJ3/bCXYiJ/5DhIQ157eJE/hZnOib9IYN8JxD2Zzv+G6Mo5Ut1A92YSjxhED3kcJdi3GrM/InNrhkMBy4lMqhe0b7WC5SWBpQnMYL0Nev9yWE1/Y8LOTM/g9zAcLuuVPuQtnS1PVIbA/ojMf2GYpbZAZD4GN4xxlZzPUcafNJQEnpzA+JOM8KyhfV2wDOBbL3jIez3ggswn99DzZrg/IjOz0Fo4JyMXlWnofmU0//NWTeb+1ATWm5MBvK/dQED04gc45ywQoqIw56cuK/N7OgL7IzKYYtAIeilFAQPiZtGFEOk9hlk+XR1kTltCYF2RgWej5689y4v2BPBLDpUdon+3JYWlGU9GYI9EJnji8kVEC9bWRG+GfXAxvumGizQLbpQncwkzIgH1CEyvGuGcZ/G7y7j+TD2/bsLivRIZYMGbYjUdxqf8NTSbgM00SGB3CUxhndRCoUkHAoiAAL5JY3c9v6hkeyYyAQ7xzYv+uybq0WKxAxgnJqzvXBuzqMLwOAkUE3AxHV2i8+YgXOWv48Bow+Q7AYuR7cERJUVmD/zCIpIACZDAThCgyOyEG1kIEiABEthOAhSZ7fQLrSIBEiCBnSBAkdkJN7IQJEACJLCdBCgy2+kXWkUCJEACO0GAIrMTbmQhSIAESGA7CVBkttMvtIoESIAEdoIARWYn3MhCkAAJkMB2EqDIbKdfaBUJkAAJ7AQBisxOuJGFIAESIIHtJECR2U6/0CoSIAES2AkCFJmdcCMLQQIkQALbSYAis51+oVUkQAIksBMEKDI74UYWggRIgAS2kwBFZjv9QqtIgARIYCcIUGR2wo0sBAmQAAlsJwGKzHb6hVaRAAmQwE4QoMjshBtZCBLYIgL3YwzfG+HXMU04W2QaTXl6AhSZp2fOHElgNwk8zGCfN1HTNGjRf4rMbjp7+VJRZJZnxTNJgARyCbiYjvpovgjERTd6GJw3Q6GhyOQi26OdFJk9cjaLSgKVEPBs9HQhMDoanxy4AGY3FJlKWCuYqHIiMz4/DJ6QGgNMC4FPMXgdPFU1rnPOEt36zx00j2rh01YN9eMOLkdT/wYpTBbiie0SnWMDB/5NFeRROzJgnPThiLuL/0hg7wh4sM/aGHyPbwCKzN5VgsICKycy+DlAwx/vPUT/rqBcd30c+ue0Yd1nzrm30TsKxEHTD2C8NmBEYqOhdmIViNcU1okUpfD6aNxZ/G5i+DuTF3+SwJ4SoMjsqeNziq2eyGCKQSNo5A/PxzlFAsYXYW/n3SjTM5HX6mhcjNPHZqNIfBpX870f12oHvZ6jDoZ3LrxEzp47w+R2jFlyZ+I4N0lg3whQZPbN48XlVVBkgKjB1/MmFcfovxIipKNnp1t990snCKs8sdICI/nIHlBOus5ZIGz1/03k2fxLAjtFIBaGoK7HEWLzv5s3s9Kyx2nl3aOll/LgjhFQUmSQmGjMCgmkULzqI93PcTF6F9ws3a9p8Yl96qDnD4E1MfwV7xVb0ysj6slYP4uuT1/DXySgEoFYGOZFJSs4FBmVPPu8tqopMvBgf9CDRj8zJCYDA+aH0sYww8l6f6JezMXM/a9HMf7mbcYxfxyYci5H01BrdNC/sTHJzvlkLuNPEthHArFgsSezj/5PlllRkQGiHouWnNx3QiFpYPAzWUyx7cBMTdSXP63NiYxI4s8E1lkrFVkmnvBqjS6GiciabM78TQL7RoAis28eLy6vuiKTCACQXXfP7gVzLrnhzbHI5ApIMaP5Iw8epncWLt81EoJTh3nLYbR5WNyzjwQoMvvo9fwyKywyiQVfvqjEQ2htK47Xj4s9w/A46L1IUYqPPWLLm2L4Nhy6Ox6ifDr0EfnwUhKomEAsDOW9fNF7X3QPxWlxuKxit2198kqLDO4ttP0hsAYG3+Wq4w5GeRqTmrw34fzZoG9uzWB+SDczwQYbzINJkUDFBGJhoMhUjHqvkldbZBIBAI1Gw2/o9Q92ag1Lypv3I3TCyX/d6GJwO4X3IM/w4P4aw7ruonmefW+sC+eLBefHDK6bHhLzfjm4DHsypXnLbPiXBHaQgOe6cBP/J1fytTI9jBL73U0+3O0gx10skuIiA+DWDF8pLp6+St4CEHrPuzVhJF4Jkw3NFL/1T+ngZyAeass739931IPNSLNdvEdYpoUElrg/ZNDNWfYBbmHiPEFxAuqLDOTiSw1a7oR/jofcCazzDprGQSRQ+ksDzXeXsO7yZlVcONc9/51lxstw/sW/aYJ3nvVvHMyiHlFOftxFAjtNgCKz0+59ZOHUFxnPgRmu8O98KZiMeSQkXk4CJEACJLAeAcVFxoNzVg8m3ZftxazHiVeRAAmQAAmsQUBdkbmfwPoYfuJVb829BmYNFryEBEiABEhgwwQUE5l4QWU0Aa8bXAS54UrB5EiABEhgUwSUFRkxUd8+szDhNMym6gLTIQESIIGNE1BMZDZefiZIAiRAAiRQIQGKTIVwmTQJkAAJ7DsBisy+1wCWnwRIgAQqJECRqRAukyYBEiCBfSdAkdn3GsDykwAJkECFBCgyFcJl0iRAAiSw7wQoMvteA1h+EiABEqiQAEWmQrhMmgRIgAT2nQBFZt9rAMtPAiRAAhUSoMhUCJdJkwAJkMC+E6DI7HsNYPlJgARIoEICFJkK4TJpEiABEth3AhSZfa8BLD8JkAAJVEiAIlMhXCZNAiRAAvtOgCKz7zWA5ScBEiCBCglQZCqEy6RJgARIYN8JUGT2vQaw/CRAAiRQIQGKTIVwmTQJkAAJ7DsBisy+1wCWnwRIgAQqJECRqRAukyYBEiCBfSdAkdn3GsDykwAJkECFBCgyFcJl0iRAAiSw7wQoMvteA1h+EiABEqiQAEWmQrhMmgRIgAT2ncD/BzcLbQlh5JHFAAAAAElFTkSuQmCC"
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"
    }
   },
   "cell_type": "markdown",
   "id": "2daa292c-26a7-4c1d-98bc-27e0f46cf360",
   "metadata": {},
   "source": [
    "![image.png](attachment:8c377443-f23d-4544-848a-ebc10446966e.png)\n",
    "![image.png](attachment:02a80467-e7d8-4a86-849e-64a68cc7ecc8.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "id": "80e3b112-4b0e-4978-8a61-01ec1139d3d8",
   "metadata": {},
   "outputs": [],
   "source": [
    "sDf.to_excel('result1_3.xlsx',index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f18b0da-8f6d-4214-92e4-fd76fe19226e",
   "metadata": {},
   "source": [
    "# 其他\n",
    "\n",
    "## （1）  long-customer-test.csv Age属性数据处理\n",
    "\n",
    "> 说明：执行任务5前需要的预处理。任务5 中用到该文件，此处是对其Age属性进行一些预处理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7430e461-5a80-4b4a-8f84-8dbbfd832197",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CustomerId</th>\n",
       "      <th>CreditScore</th>\n",
       "      <th>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Tenure</th>\n",
       "      <th>Balance</th>\n",
       "      <th>NumOfProducts</th>\n",
       "      <th>HasCrCard</th>\n",
       "      <th>IsActiveMember</th>\n",
       "      <th>EstimatedSalary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>15647311</td>\n",
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       "      <td>83807.86</td>\n",
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       "      <td>1</td>\n",
       "      <td>112542.58</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>15737452</td>\n",
       "      <td>653</td>\n",
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       "      <td>1</td>\n",
       "      <td>132602.88</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5097.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>15577657</td>\n",
       "      <td>732</td>\n",
       "      <td>0</td>\n",
       "      <td>41</td>\n",
       "      <td>8</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>170886.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>15589475</td>\n",
       "      <td>591</td>\n",
       "      <td>1</td>\n",
       "      <td>39</td>\n",
       "      <td>3</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>140469.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>15687946</td>\n",
       "      <td>556</td>\n",
       "      <td>1</td>\n",
       "      <td>61</td>\n",
       "      <td>2</td>\n",
       "      <td>117419.35</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>94153.83</td>\n",
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       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>15732202</td>\n",
       "      <td>615</td>\n",
       "      <td>0</td>\n",
       "      <td>34</td>\n",
       "      <td>1</td>\n",
       "      <td>83503.11</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>73124.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>15735078</td>\n",
       "      <td>724</td>\n",
       "      <td>1</td>\n",
       "      <td>53</td>\n",
       "      <td>1</td>\n",
       "      <td>139687.66</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12913.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>15707861</td>\n",
       "      <td>520</td>\n",
       "      <td>1</td>\n",
       "      <td>46</td>\n",
       "      <td>10</td>\n",
       "      <td>85216.61</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>117369.52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>15594612</td>\n",
       "      <td>702</td>\n",
       "      <td>0</td>\n",
       "      <td>44</td>\n",
       "      <td>9</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>59207.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>15806360</td>\n",
       "      <td>609</td>\n",
       "      <td>0</td>\n",
       "      <td>41</td>\n",
       "      <td>6</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>112585.19</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     CustomerId  CreditScore  Gender  Age  Tenure    Balance  NumOfProducts  \\\n",
       "0      15647311          608       1   41       1   83807.86              1   \n",
       "1      15737452          653       0   58       1  132602.88              1   \n",
       "2      15577657          732       0   41       8       0.00              2   \n",
       "3      15589475          591       1   39       3       0.00              3   \n",
       "4      15687946          556       1   61       2  117419.35              1   \n",
       "..          ...          ...     ...  ...     ...        ...            ...   \n",
       "995    15732202          615       0   34       1   83503.11              2   \n",
       "996    15735078          724       1   53       1  139687.66              2   \n",
       "997    15707861          520       1   46      10   85216.61              1   \n",
       "998    15594612          702       0   44       9       0.00              1   \n",
       "999    15806360          609       0   41       6       0.00              1   \n",
       "\n",
       "     HasCrCard  IsActiveMember  EstimatedSalary  \n",
       "0            0               1        112542.58  \n",
       "1            1               0          5097.67  \n",
       "2            1               1        170886.17  \n",
       "3            1               0        140469.38  \n",
       "4            1               1         94153.83  \n",
       "..         ...             ...              ...  \n",
       "995          1               1         73124.53  \n",
       "996          1               1         12913.92  \n",
       "997          1               0        117369.52  \n",
       "998          0               0         59207.41  \n",
       "999          0               1        112585.19  \n",
       "\n",
       "[1000 rows x 10 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lTestDf=pd.read_csv('B题：银行客户忠诚度分析赛题数据/long-customer-test.csv')\n",
    "lTestDf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b45c0a19-7355-4537-8bf7-7ecb46425f0f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([41, 58, 39, 61, 33, 34, 46, 24, 48, 37, 57, 28, 73, 31, 44, 30, 26,\n",
       "       72, 40, 35, 27, 36, 49, 42, 32, 45, 38, 25, 47, 56, 51, 43, 62, 18,\n",
       "       63, 53, 64, 67, 29, 52, 50, 23, 54, 55, 20, 74, 22, 59, 70, 71, 85,\n",
       "       60, 66, 68, 77, 19, 21, 69], dtype=int64)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lTestDf['Age'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7fc35ca4-eec4-4e0f-825b-b97df6dcabd6",
   "metadata": {},
   "source": [
    "> 说明：发现long-customer-test.csv 文件中 Age属性不存在类似long-customer-train.csv文件中Age属性中的问题，所以无需处理Age属性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0906200d-7473-4291-9e5b-940adcbd0253",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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